IOS2020: INFORMS OPTIMIZATION SOCIETY CONFERENCE 2020

This page contains an index consisting of author-provided keywords.

A
A-optimality	Approximation Algorithms for the Maximum Entropy Sampling Problem
Accelaration	Using Effective Scenarios to Accelerate Decomposition Algorithms for Two-stage Distributionally Robust Optimization with Total Variation Distance
Acceleration	Sliding Linearized ADMM For Convex Smooth Optimization With Affine Constraints
Ackley function	Strong contraction mapping and topological non-convex optimization
active learning	Optimal Decision Tree with Noisy Outcomes Tutorial: A Unified Framework for Sequential Decisions under Uncertainty
adaptive algorithm	Reinforcement Learning under Drift: The Blessing of (More) Optimism
Adaptive Dose-Finding	Personalized Dose Finding Trials
Adiabatic Quantum Computing	Template-based Minor Embedding for Adiabatic Quantum Optimization
ADMM	Sliding Linearized ADMM For Convex Smooth Optimization With Affine Constraints In Memory of Dave Shanno: Objective Bounds from ADMM Algorithms
Agricultural products	Global Supply Chain Networks and Tariff Rate Quotas: Equilibrium Analysis with Application to Agricultural Products
Algebraic geometry	Integer programming techniques for minor-embedding in quantum annealers
algorithm	A Study on the Block Relocation Problem: Lower Bound Derivations and Strong Formulations
Algorithmic Fairness	Exploring Algorithmic Fairness in Robust Graph Covering Problems
Alternating Direction Method of Multipliers	Understanding Limitation of Two Symmetrized Orders by Worst-case Complexity Acceleration of Primal-Dual Methods by Preconditioning and Simple Subproblem Procedures
analytics	Learning to optimize with hidden constraints
appointment scheduling	A distributionally robust optimization approach for outpatient colonoscopy scheduling Data-Driven Distributionally Robust Appointment Scheduling
Approximate dynamic programming	Self-guided Approximate Linear Programs
approximate linear programming	Self-guided Approximate Linear Programs Adaptive Approximate Linear Programs based on Index Networks for Solving Weakly-coupled Dynamic Programs
Approximation	Multilevel algorithms for geographical districting problems
Approximation algorithms	Optimal Decision Tree with Noisy Outcomes
Assortment Planning	Optimizing Revenue while Showing Relevant Recommendations Robust Assortment Optimization under Product Unavailability
asymptote	Weak infeasibility in semidefinite programming: a complete characterization and generating all instances
Asymptotic Analysis	Personalized Dose Finding Trials
Asymptotic Convergence	Data-Driven Robust MDPs Using Distance-Based Ambiguity Sets
B
barriers to discharge	Machine Learning to Address Hospital Capacity: Predicting Discharges and Identifying Barriers to Discharge
Bayesian	Partially observable multistage stochastic programming
Belief Propagation	The Potential of Quantum Annealing for Rapid Solution Structure Identification
Bender's decomposition	Using Effective Scenarios to Accelerate Decomposition Algorithms for Two-stage Distributionally Robust Optimization with Total Variation Distance
Benders	Network Interdiction with Asymmetric Cost Uncertainty
Benders decomposition	Stochastic Team Formation Problem Conic Formulations for a Mean-Risk Stochastic Mixed Integer Nonlinear Program with Applications to Network Protection The Star Degree Centrality Problem: A Benders Decomposition Approach Benders Cut Classification via Support Vector Machines for Solving Two-stage Stochastic Programs
Best subset selection	A mixed-integer optimization approach for exhaustive cross-validated model selection
betweenness centrality	Centralities for Networks with Consumable Resources
Bi-level model	Estimating Wireless Mesh Network Vulnerability: A Search for the “Best” Interference Model
bi-objective	Bi-objective multistage stochastic linear programming
biased stochastic approximation	Biased Stochastic Approximation for Conditional Stochastic Optimization
Big-M Bounds	A mixed-integer optimization approach for exhaustive cross-validated model selection
Bilevel optimization	Dualization and Bilevel optimization in JuMP
bilevel programming	A bilevel programming model for coordinating product transitions
bilinear problem	Inverse Markov decision process with unknown transition probabilities
Bimodal service duration	A distributionally robust optimization approach for outpatient colonoscopy scheduling
bin packing	Optimization Algorithms for the Bin Packing Problem with Minimum Color Fragmentation
Binary Optimization	A Combinatorial Cut-and-Lift Procedure with an Application to 0-1 Chance Constraints
blind deconvolution	Implicit Regularization in Nonconvex Statistical Estimation: Gradient Descent Converges Linearly for Phase Retrieval, Matrix Completion, and Blind Deconvolution Composite optimization for blind deconvolution Structured local minima in some nonconvex optimization problems
block relocation problem	A Study on the Block Relocation Problem: Lower Bound Derivations and Strong Formulations
bounding	Subtree Decomposition Method For Multistage Stochastic Programs
Bounds tightening	Decomposing Optimization-Based Bounds Tightening Problems Via Graph Partitioning
branch and price	Optimization Algorithms for the Bin Packing Problem with Minimum Color Fragmentation
Branch-and-Bound	Achieving Consistency with Cutting Planes
Branch-and-Bound Algorithm	Maximizing the total pleasure from a personalized day tour
branch-and-cut	Scenario grouping and decomposition algorithms for chance-constrained programs Minimum blockers for the set covering problem A Branch-and-Cut Approach For Simple Graph Partitioning on Sparse Graphs
Branch-and-cut algorithm	Estimating Wireless Mesh Network Vulnerability: A Search for the “Best” Interference Model
branch-and-price	A Team Orienteering Problem for Fixed-Wing Drones
Branching	Spectral relaxations and branching for MIQPs
breast cancer screening	Data-driven optimization of supplemental screening usage in breast cancer detection
breast density information	Data-driven optimization of supplemental screening usage in breast cancer detection
C
Car-sharing	Lookahead-bounded Q-learning
Casual Inference	Causal Inference with Selectively-Deconfounded Data
causal inference	Safely Learning to Personalize from Sequential Observational Data
Chance Constraints	A Combinatorial Cut-and-Lift Procedure with an Application to 0-1 Chance Constraints Joint chance-constrained programs and the intersection of mixing sets through a submodularity lens
chance-constrained programming	Scenario grouping and decomposition algorithms for chance-constrained programs
Classification	Boolean Decision Rules via Column Generation Engineering fast multilevel support vector machines Learning Sparse Classifiers: Continuous and Mixed Integer Optimization Perspectives
Cloud computing	Dynamic Resource Allocation in the Cloud with Near-Optimal Efficiency
color fragmentation	Optimization Algorithms for the Bin Packing Problem with Minimum Color Fragmentation
column generation	The RIP Technique for Box Configuration for Birchbox
Column-and-Constraint Generation	A Distributionally Robust Optimization Approach for Stochastic Elective Surgery Scheduling with Limited ICU Capacity
Combinatorial constraints	On the convexification of constrained quadratic optimization problems with indicator variables
combinatorial multi-armed bandits	Adaptive Approximate Linear Programs based on Index Networks for Solving Weakly-coupled Dynamic Programs
combinatorial optimization	Ranking-based Facet Defining Inequalities for the Weak Order Polytope Solving Multi-Objective Combinatorial Cell Formation Problem: A Two-Step Approach Using A Distance Function and A Genetic Algorithm Optimization Algorithms for the Bin Packing Problem with Minimum Color Fragmentation
Combinatorial Optimization Hardware	On Modeling Local Search with Special-Purpose Combinatorial Optimization Hardware
combinatorial structure	Electrical Flows over Spanning Trees
competitive analysis	Impact of Bias on Hiring Decisions
competitive ratio	The Competitive Ratio of Threshold Policies for Online Unit-density Knapsack Problems
Complexity	Complexity of stochastic dual dynamic programming Tractable Reformulations of Distributionally Robust Two-stage Stochastic Programs with $\infty-$Wasserstein Distance
Complexity analysis	Complexity of proximal augmented Lagrangian for nonconvex optimization with nonlinear equality constraints
Composite optimization	Composite optimization for blind deconvolution Low-rank matrix recovery with composite optimization: good conditioning and rapid convergence
Computational Social Choice	Ranking-based Facet Defining Inequalities for the Weak Order Polytope
concave subcontracting costs	Exact Algorithms for Lot-Sizing Problems with Multiple Capacities, Piecewise Concave Production Costs, and Subcontracting
Concentration inequalities	An MINLP approach to bounding probability with applications to Network routing
Conditional Gradient	Zeroth-order Nonconvex Stochastic Optimization: Handling Constraints, High-Dimensionality, and Saddle-Points
Conditional Value-at-Risk	Conic Formulations for a Mean-Risk Stochastic Mixed Integer Nonlinear Program with Applications to Network Protection
conic	Hypatia: formulations, linear algebra, and preliminary computational results
conic mixed integer rounding	(Partial) Convex Hull for Deterministic and Stochastic Structured Conic Mixed Integer Sets using Conic Mixed Integer Rounding
conic optimization	Data-Driven Two-Stage Conic Optimization with Rare High-Impact Zero-One Uncertainties Disjunctive cuts for Mixed-Integer Conic Optimization Hypatia: Generic Nonsymmetric Conic Optimization in Julia Strong formulations for sparse regression
Conic programming	Subadditive Duality for Conic Mixed-Integer Programs
Conjugate Gradient methods	New Multi-Step Conjugate Gradient Method for Optimization
Consistency	Achieving Consistency with Cutting Planes
Constrained Optimization	Level-Set Method for Convex Constrained Optimization with Error Bound Conditions
Constrained Stochastic Optimization	A Data Efficient and Feasible Level Set Method for Stochastic Convex Optimization with Expectation Constraints
constraint programming	Improving Operating Room Scheduling: Integer and Constraint Programming Approaches Achieving Consistency with Cutting Planes University timetabling problem with requested instructor workload using constraint program
container	A Study on the Block Relocation Problem: Lower Bound Derivations and Strong Formulations
continuous optimization	Hypatia: formulations, linear algebra, and preliminary computational results
Control solution	Control and tolerance two-sided interval linear programming problems
Convergence analysis	Online Primal-Dual Mirror Descent under Stochastic Constraints
convergence rate	Data-driven sample average approximation with covariate information
Convex approximations	Solving risk-averse mixed-integer stochastic programs using convex approximations
Convex hull	On the tightness of SDP relaxations of QCQPs
convex optimization	Aspects of maximum-entropy sampling Sliding Linearized ADMM For Convex Smooth Optimization With Affine Constraints Powerful Operator Splitting with Projective Splitting
Convex quadratic programs	Spectral relaxations and branching for MIQPs
convex relaxation	Bridging Convex and Nonconvex Optimization in Robust PCA: Noise, Outliers, and Missing Data On SDP formulations for quadratic optimization with indicator variables
Convex-concave minimax optimization	Near-Optimal Algorithms for Smooth Convex-Concave Minimax Optimization and Beyond
Convexification	Outlier detection in time series via mixed-integer conic quadratic optimization On the convexification of constrained quadratic optimization problems with indicator variables
Coordinate descent	Understanding Limitation of Two Symmetrized Orders by Worst-case Complexity Coordinate Descent Without Coordinates: Tangent Subspace Descent on Riemannian Manifolds
cost and time buffers	Earned Value Measurement in Project Buffers Management
course scheduling	University timetabling problem with requested instructor workload using constraint program
covariates	Data-driven sample average approximation with covariate information
covering tour	A multi-vehicle covering tour problem with speed optimization
Cross-validation	Data-driven sample average approximation with covariate information A mixed-integer optimization approach for exhaustive cross-validated model selection
Cubic binary optimization	A Heuristic and Exact Solution Approach for the 0-1 Cubic Knapsack Problem
cut classification	Benders Cut Classification via Support Vector Machines for Solving Two-stage Stochastic Programs
Cut management	Using Effective Scenarios to Accelerate Decomposition Algorithms for Two-stage Distributionally Robust Optimization with Total Variation Distance
Cut-and-Lift	A Combinatorial Cut-and-Lift Procedure with an Application to 0-1 Chance Constraints
Cutting plane methods	A Sequential Sampling Method for Distributionally Robust Linear Programs
Cutting Planes	Achieving Consistency with Cutting Planes
Cutting-Plane Algorithms	Inverse Mixed-Integer Optimization with Trust-Region Methods
cystic fibrosis	Equity in Genetic Newborn Screening
D
Data-driven ambiguity set	Data-Driven Robust MDPs Using Distance-Based Ambiguity Sets
data-driven optimization	Coupled Learning Enabled Stochastic Programming with Endogenous Uncertainty
Data-driven prescriptive analytics	A Data-Driven Approach for a Class of Stochastic Dynamic Optimization Problems
Data-driven stochastic programming	Data-driven sample average approximation with covariate information
data-integrated modeling	Data-Driven Optimization for Team Formation
Dave Shanno	Reflections on Dave Shanno Remembering Dave Shanno: Twenty Years of Collaboration In Memory of Dave Shanno: making an interior-point method for NLP converge In Memory of Dave Shanno: the History of OB1 In memory of Dave Shanno: Revisiting Quasi-Newton Methods In Memory of Dave Shanno: Objective Bounds from ADMM Algorithms Solving the Problem of Portfolio VAR Minimization as a Nonlinear Program In memory of Dave Shanno: from optimization to machine learning, it’s all the same data
DDPG	Comparing model-free and model-based methods for multistage stochastic programming
decentralized decisions	A bilevel programming model for coordinating product transitions
Decision diagrams	A Combinatorial Cut-and-Lift Procedure with an Application to 0-1 Chance Constraints Optimization Algorithms for the Bin Packing Problem with Minimum Color Fragmentation On parametric decision diagrams Last mile scheduling under uncertainty
Decision making	Wasserstein Distributionally Robust Inverse Multiobjective Optimization
Decision Making under Uncertainty	Interval Linear Programming with an Additional Function of Interest: Computational Complexity, Reformulations, and Heuristics
Decomposition	Decomposing Optimization-Based Bounds Tightening Problems Via Graph Partitioning Integer programming techniques for minor-embedding in quantum annealers A Decomposition Interior-Point Algorithm for Stochastic Linear Optimization in a Hilbert Space
decomposition algorithms	On the Values of Vehicle-to-Grid Electricity Selling in Electric Vehicle Sharing
Deep Learning	The Role of Optimization Algorithms in Generalization of Deep Learning Strong mixed-integer programming formulations for trained neural networks Lossless Compression of Deep Neural Networks Scaling Up Quasi-Newton Algorithms: Communication Efficient Distributed SR1
demand learning	Online Learning in Service Systems: Optimal Pricing And Capacity Sizing For A G/G/1 Queue With Demand Learning
Derivative-free optimization	Surrogate Optimization of Deep Neural Networks for Groundwater Predictions
Diagonal perturbation	Neural network approximations in quadratic optimization
Difference of convex optimization	New Bregman proximal type algorithms for solving DC optimization problems
discharge prediction	Machine Learning to Address Hospital Capacity: Predicting Discharges and Identifying Barriers to Discharge
Discrete Optimization	Aspects of maximum-entropy sampling Inverse Mixed-Integer Optimization with Trust-Region Methods JANOS : An Integrated Predictive and Prescriptive Modeling Framework The Potential of Quantum Annealing for Rapid Solution Structure Identification On parametric decision diagrams
Discretization	Neural network approximations in quadratic optimization
Disjunctive Cutting Planes	Disjunctive cuts for Mixed-Integer Conic Optimization
disruption intensity	A Stochastic Programming Model with Endogenous and Exogenous Uncertainty for Reliable Network Design Under Random Disruption
Distance Function	Solving Multi-Objective Combinatorial Cell Formation Problem: A Two-Step Approach Using A Distance Function and A Genetic Algorithm
distributed optimization	Scaling Up Quasi-Newton Algorithms: Communication Efficient Distributed SR1 Decentralized Computation of Effective Resistances for Distributed Learning A Dual Approach for Optimal Algorithms in Distributed Optimization over Networks Distributed Algorithms for Multi-Scale Capacity Expansion Problems in Power Systems
distribution network	Optimal Power Flow in Distribution Networks under Stochastic N-1 Disruptions
Distributionally robust	Wasserstein Distributionally Robust Inverse Multiobjective Optimization
Distributionally robust dynamic optimization	A Data-Driven Approach for a Class of Stochastic Dynamic Optimization Problems
Distributionally robust optimization	Tractable Reformulations of Distributionally Robust Two-stage Stochastic Programs with $\infty-$Wasserstein Distance Data-Driven Two-Stage Conic Optimization with Rare High-Impact Zero-One Uncertainties A Sequential Sampling Method for Distributionally Robust Linear Programs Distributionally Robust Stochastic Dual Dynamic Programming Using Effective Scenarios to Accelerate Decomposition Algorithms for Two-stage Distributionally Robust Optimization with Total Variation Distance Nurse Staffing under Absenteeism: A Distributionally Robust Optimization Approach A Distributionally Robust Optimization Approach for Stochastic Elective Surgery Scheduling with Limited ICU Capacity A distributionally robust optimization approach for outpatient colonoscopy scheduling Distributionally Robust Transmission Grid under Geomagnetic Disturbances Data-Driven Distributionally Robust Appointment Scheduling
Districting	Multilevel algorithms for geographical districting problems
Domain reduction	Decomposing Optimization-Based Bounds Tightening Problems Via Graph Partitioning
Downstream Resource Constraints	A Distributionally Robust Optimization Approach for Stochastic Elective Surgery Scheduling with Limited ICU Capacity
drone	Robust two echelon vehicle and drone routing for humanitarian relief operations
drone routing	A Team Orienteering Problem for Fixed-Wing Drones
drug shortages	Adaptive Pharmaceutical Supply Chain Design under Disruption and its Effects on Drug Shortages
dual threshold	On Polyhedra of Two Influence Maximization Problems in Social Networks
Duality	Subadditive Duality for Conic Mixed-Integer Programs
Dubins’ vehicles	A Team Orienteering Problem for Fixed-Wing Drones
dynamic optimization	A Model of the Online Independent Set Problem
dynamic pricing	Meta Dynamic Pricing: Learning Across Experiments
dynamic programming	Complexity of stochastic dual dynamic programming Dynamic Tuberculosis Screening for Healthcare Employees Exact Algorithms for Lot-Sizing Problems with Multiple Capacities, Piecewise Concave Production Costs, and Subcontracting Network Models for Multiobjective Discrete Optimization Tutorial: A Unified Framework for Sequential Decisions under Uncertainty A Branch-and-Cut Approach For Simple Graph Partitioning on Sparse Graphs
dynamic programming applications	Data-driven optimization of supplemental screening usage in breast cancer detection
Dynamical Systems	Learning Dynamical Systems with Side Information
E
earned value analysis	Earned Value Measurement in Project Buffers Management
effective resistances	Decentralized Computation of Effective Resistances for Distributed Learning
electric vehicle sharing	On the Values of Vehicle-to-Grid Electricity Selling in Electric Vehicle Sharing
electrical flows	Electrical Flows over Spanning Trees
elementary reformulation	Weak infeasibility in semidefinite programming: a complete characterization and generating all instances
Emerald ash borer	Incentivizing Homeowners for Tree Management using a Principal-Agent Game-Theoretical Approach
empirical risk minimization	Sample Complexity of Sample Average Approximation for Conditional Stochastic Optimization Decentralized Computation of Effective Resistances for Distributed Learning
end-to-end	Risk Guarantees For End-to-end Prediction and Optimization Processes
endogenous uncertainty	Stochastic Team Formation Problem Robust Optimization with Decision-Dependent Information Discovery Optimal Active Preference Elicitation via Adjustable Robust Optimization Nurse Staffing under Absenteeism: A Distributionally Robust Optimization Approach A Stochastic Programming Model with Endogenous and Exogenous Uncertainty for Reliable Network Design Under Random Disruption
energy systems	On the Values of Vehicle-to-Grid Electricity Selling in Electric Vehicle Sharing
entropy	Aspects of maximum-entropy sampling
entrywise guarantee	Bridging Convex and Nonconvex Optimization in Robust PCA: Noise, Outliers, and Missing Data
equity	Equity in Genetic Newborn Screening
Error Bound Condition	Level-Set Method for Convex Constrained Optimization with Error Bound Conditions
Exactness	On Sufficient and Necessary Conditions for Rank-One Generated Cones
F
Facility location	Optimal location of last-mile consolidation areas to reduce environmental impact of urban deliveries of goods: a heuristic approach Data-driven optimization for wind farm siting
Feasibility	A Data Efficient and Feasible Level Set Method for Stochastic Convex Optimization with Expectation Constraints
feature engineering	Categorical Feature Compression via Submodular Optimization
Finance	Solving the Problem of Portfolio VAR Minimization as a Nonlinear Program
Finite-sample guarantees	Data-Driven Robust MDPs Using Distance-Based Ambiguity Sets
Finite-sum composition	Katyusha Acceleration for Convex Finite-Sum Compositional Optimization
Firefly optimization algorithm	Bi-Objective Firefly Optimization Algorithm for n-Stage Parallel Machine Scheduling
First-Order Methods	An $O(s^r)$-Resolution ODE Framework for Discrete-Time Optimization Algorithms and Applications to Convex-Concave Saddle-Point Problems First-order methods for large-scale linear programming Radial Duality Powerful Operator Splitting with Projective Splitting
fixed-charge generalized network	Extreme-point Tabu Search Heuristic for Fixed-Charge Generalized Transshipment Problems
fixed-charge generalized transshipment network heuristic	Extreme-point Tabu Search Heuristic for Fixed-Charge Generalized Transshipment Problems
Fixed-point theorems	Strong contraction mapping and topological non-convex optimization
fixed-wing drones	A Team Orienteering Problem for Fixed-Wing Drones
flow machine learning	Integrated Learning and Optimization for AC-OPF
Flow shop scheduling	Developing an Efficient Exact Solution Approach for Scheduling Problems
folded concave penalty	Provable Generalizability of Deep Neural Networks under Sparsity-Inducing Regularization
Forecasting	Spatio-temporal forecasting for wind energy and its impact on wind farm operations
formulation	The RIP Technique for Box Configuration for Birchbox
Formulations	Strong mixed-integer programming formulations for trained neural networks
Functional Constraints	Level-Set Method for Convex Constrained Optimization with Error Bound Conditions
G
generalizability of neural network	Provable Generalizability of Deep Neural Networks under Sparsity-Inducing Regularization
Generalized eigenvalue	Spectral relaxations and branching for MIQPs
Genetic Algorithms	Solving Multi-Objective Combinatorial Cell Formation Problem: A Two-Step Approach Using A Distance Function and A Genetic Algorithm
Genetic testing	Equity in Genetic Newborn Screening
Geomagnetic disturbances	Distributionally Robust Transmission Grid under Geomagnetic Disturbances
Global optimization	Aspects of maximum-entropy sampling Spectral relaxations and branching for MIQPs Strong contraction mapping and topological non-convex optimization
Global trade	Global Supply Chain Networks and Tariff Rate Quotas: Equilibrium Analysis with Application to Agricultural Products
gradient descent	Convergent variants of gradient descent for neural networks Implicit Regularization in Nonconvex Statistical Estimation: Gradient Descent Converges Linearly for Phase Retrieval, Matrix Completion, and Blind Deconvolution
graph clustering	Multistart Methods for Quantum Approximate Optimization
Graph contraction	Multilevel algorithms for geographical districting problems
Graph Embedding	Partition Hypergraphs with Embeddings
graph mining	Network Alignment by Propagating Reliable Similarities
Graph minors	Integer programming techniques for minor-embedding in quantum annealers
graph partitioning	Partition Hypergraphs with Embeddings A Branch-and-Cut Approach For Simple Graph Partitioning on Sparse Graphs
Greedy heuristic	Optimal location of last-mile consolidation areas to reduce environmental impact of urban deliveries of goods: a heuristic approach
Groundwater prediction	Surrogate Optimization of Deep Neural Networks for Groundwater Predictions
Group Efficacy	Solving Multi-Objective Combinatorial Cell Formation Problem: A Two-Step Approach Using A Distance Function and A Genetic Algorithm
H
health care	The Outcome Range Problem in Interval Linear Programming
healthcare	Safely Learning to Personalize from Sequential Observational Data Adaptive Pharmaceutical Supply Chain Design under Disruption and its Effects on Drug Shortages Learning to optimize with hidden constraints Precision Heparin Dosing using Mixed Integer Optimization
heuristic	A Heuristic and Exact Solution Approach for the 0-1 Cubic Knapsack Problem
Heuristics	Developing an Efficient Exact Solution Approach for Scheduling Problems Interval Linear Programming with an Additional Function of Interest: Computational Complexity, Reformulations, and Heuristics The Outcome Range Problem in Interval Linear Programming
Hidden Markov models	A Data-Driven Approach for a Class of Stochastic Dynamic Optimization Problems
Hierarchical method	Engineering fast multilevel support vector machines
High performance computing	Data driven stochastic optimization applied to renewable energy penetration in power systems
Hilbert space	A Decomposition Interior-Point Algorithm for Stochastic Linear Optimization in a Hilbert Space
Huge Scale	First-order methods for large-scale linear programming
Human Trafficking	Integer Programming Methods to Alleviate Human Trafficking in Maritime Settings
Humanitarian Logistics	Integer Programming Methods to Alleviate Human Trafficking in Maritime Settings
humanitarian relief	Robust two echelon vehicle and drone routing for humanitarian relief operations
humanitarian supply chain	Robust two echelon vehicle and drone routing for humanitarian relief operations
hydropower	Comparing model-free and model-based methods for multistage stochastic programming
Hypergraphs	Partition Hypergraphs with Embeddings
Hyperparameter optimization	Surrogate Optimization of Deep Neural Networks for Groundwater Predictions
I
illposedness	Weak infeasibility in semidefinite programming: a complete characterization and generating all instances
Imbalanced learning	Engineering fast multilevel support vector machines
implicit bias	Impact of Bias on Hiring Decisions
implicit regularization	The Role of Optimization Algorithms in Generalization of Deep Learning
Independent Set	Exploiting Multiple Optimal Solutions in Independent Set A Model of the Online Independent Set Problem
Indicator variables	On the convexification of constrained quadratic optimization problems with indicator variables
inexact data	The Outcome Range Problem in Interval Linear Programming
influence maximization	On Polyhedra of Two Influence Maximization Problems in Social Networks
Information relaxation	Lookahead-bounded Q-learning
infrastructure protection	A Stochastic Programming Model with Endogenous and Exogenous Uncertainty for Reliable Network Design Under Random Disruption
integer	Volumetric Analysis of Perspective Reformulations
Integer Column Generation	An Integer Column Generation Procedure for Coordinating Product Transitions in Semiconductor Manufacturing using Combinatorial Auctions
Integer Linear Programming	Template-based Minor Embedding for Adiabatic Quantum Optimization
Integer programing	On parametric decision diagrams
Integer Programming	Data driven stochastic optimization applied to renewable energy penetration in power systems Exploiting Multiple Optimal Solutions in Independent Set Exploiting almost identical generators in unit commitment Improving Operating Room Scheduling: Integer and Constraint Programming Approaches Integer Programming Methods to Alleviate Human Trafficking in Maritime Settings Achieving Consistency with Cutting Planes Robust Optimization with Decision-Dependent Information Discovery Network Models for Multiobjective Discrete Optimization Boolean Decision Rules via Column Generation Joint chance-constrained programs and the intersection of mixing sets through a submodularity lens Integer programming techniques for minor-embedding in quantum annealers The Potential of Quantum Annealing for Rapid Solution Structure Identification Optimization Algorithms for the Bin Packing Problem with Minimum Color Fragmentation Variance Reduction in Stochastic Programming and Applications in Logistics
Inter-optimal polyhedron	Developing an Efficient Exact Solution Approach for Scheduling Problems
Interactions	Sparse Regression with Interactions: A Scalable Integer Programming Approach
Interative methods	Low-rank matrix recovery with composite optimization: good conditioning and rapid convergence
Interdependent Infrastructures	A Reserve Scheduling Framework for Uncertainty Management in Power Systems and Gas Pipelines
interdiction	Minimum blockers for the set covering problem Network Interdiction with Asymmetric Cost Uncertainty
Interdiction games	A Progressive approximation approach for the exact solution of sparse large-scale binary interdiction games
Interference models	Estimating Wireless Mesh Network Vulnerability: A Search for the “Best” Interference Model
interior point	Hypatia: formulations, linear algebra, and preliminary computational results
Interior point method	Hypatia: Generic Nonsymmetric Conic Optimization in Julia
Interior Point Methods	Remembering Dave Shanno: Twenty Years of Collaboration In Memory of Dave Shanno: making an interior-point method for NLP converge In Memory of Dave Shanno: the History of OB1 Learning to optimize with hidden constraints
Interior-point methods	A Decomposition Interior-Point Algorithm for Stochastic Linear Optimization in a Hilbert Space
Internal to External set up	Developing a Mixed Integer Linear Program (MILP) to maximize material utilization and switch the setup from internal to external
Interpretable policy	Learning Interpretable Policies for Markov Decision Process by Hybrid Linear-Black-Box Model
interval analysis	Interval Linear Programming with an Additional Function of Interest: Computational Complexity, Reformulations, and Heuristics The Outcome Range Problem in Interval Linear Programming
interval linear programming	Interval Linear Programming with an Additional Function of Interest: Computational Complexity, Reformulations, and Heuristics The Outcome Range Problem in Interval Linear Programming
Interval linear system	Control and tolerance two-sided interval linear programming problems
inventory	M-natural-convexity and its applications in operations
Inventory management	Self-guided Approximate Linear Programs
Inverse optimization	Inverse Markov decision process with unknown transition probabilities Inverse Mixed-Integer Optimization with Trust-Region Methods
Inverse problem	Low-rank matrix recovery with composite optimization: good conditioning and rapid convergence
Ising Model	On Modeling Local Search with Special-Purpose Combinatorial Optimization Hardware The Potential of Quantum Annealing for Rapid Solution Structure Identification
Iterative Combinatorial Auctions	An Integer Column Generation Procedure for Coordinating Product Transitions in Semiconductor Manufacturing using Combinatorial Auctions
Iterative method	Nonlinear Regularization for Neural Networks
J
Job sequencing and scheduling	Bi-Objective Firefly Optimization Algorithm for n-Stage Parallel Machine Scheduling
Job shop scheduling	Developing an Efficient Exact Solution Approach for Scheduling Problems
JuMP	Dualization and Bilevel optimization in JuMP
K
k-means clustering	Structured local minima in some nonconvex optimization problems
Katyusha	Katyusha Acceleration for Convex Finite-Sum Compositional Optimization
Katz centrality	Centralities for Networks with Consumable Resources
kidney exchange	Optimization Under Uncertainty in Kidney Exchange
knapsack problem	The Competitive Ratio of Threshold Policies for Online Unit-density Knapsack Problems
L
L1-norm line fitting	Approximating L1-Norm Best-Fit Lines and Extensions
L1-norm principal component analysis	Approximating L1-Norm Best-Fit Lines and Extensions
L1-norm subspace fitting	Approximating L1-Norm Best-Fit Lines and Extensions
labeling algorithm	A multi-vehicle covering tour problem with speed optimization
Lagrange function	On the tightness of SDP relaxations of QCQPs
Lagrangian relaxation	An Algorithm for Parametric Quadratically Constrained Quadratic Programs A multi-vehicle covering tour problem with speed optimization
Land use optimization	A stochastic mixed integer linear program for agricultural land use optimization
Landscape	On the Benefit of Width for Neural Networks: Disappearance of Basins
large deviations theory	Sample Complexity of Sample Average Approximation for Conditional Stochastic Optimization
Large Neighborhood Search	The Potential of Quantum Annealing for Rapid Solution Structure Identification
Large-scale optimization	Coordinate Descent Without Coordinates: Tangent Subspace Descent on Riemannian Manifolds
LASSO problems	In Memory of Dave Shanno: Objective Bounds from ADMM Algorithms
Last-mile	Last mile scheduling under uncertainty
Last-mile logistics	Optimal location of last-mile consolidation areas to reduce environmental impact of urban deliveries of goods: a heuristic approach
latently decision-dependent uncertainty	Coupled Learning Enabled Stochastic Programming with Endogenous Uncertainty
Lazy Constraints	Learning-Enhanced Integer Programming: A Hybrid Approach for Routinely Solved Discrete Optimization
Learning	Online Primal-Dual Mirror Descent under Stochastic Constraints Learning Dynamical Systems with Side Information
leave-one-out	Near-optimal bounds for phase synchronization
leave-one-out analysis	Bridging Convex and Nonconvex Optimization in Robust PCA: Noise, Outliers, and Missing Data Implicit Regularization in Nonconvex Statistical Estimation: Gradient Descent Converges Linearly for Phase Retrieval, Matrix Completion, and Blind Deconvolution
Level Set methods	A Data Efficient and Feasible Level Set Method for Stochastic Convex Optimization with Expectation Constraints
Lifting	Outlier detection in time series via mixed-integer conic quadratic optimization
linear conic optimization	Weak infeasibility in semidefinite programming: a complete characterization and generating all instances
linear convergence	A Line-Search Descent Algorithm for Strict Saddle Functions with Complexity Guarantees Nonsmooth Optimization over Stiefel Manifold: Riemannian Subgradient Methods
Linear Programming	Exploiting symmetry in linear programming First-order methods for large-scale linear programming Reflections on Dave Shanno In Memory of Dave Shanno: the History of OB1 The Outcome Range Problem in Interval Linear Programming A Decomposition Interior-Point Algorithm for Stochastic Linear Optimization in a Hilbert Space
Linearizable	Characterizing Linearizable QAPs by the Level-1 RLT
Linearization	A Heuristic and Exact Solution Approach for the 0-1 Cubic Knapsack Problem
local minima	Structured local minima in some nonconvex optimization problems
Local Search	On Modeling Local Search with Special-Purpose Combinatorial Optimization Hardware The Potential of Quantum Annealing for Rapid Solution Structure Identification Network Alignment by Propagating Reliable Similarities
local search algorithm	Approximation Algorithms for the Maximum Entropy Sampling Problem
Locality sensitive hashing	Optimizing Revenue while Showing Relevant Recommendations
low rank	Near-optimal bounds for phase synchronization
Low-rank matrix recovery	Low-rank matrix recovery with composite optimization: good conditioning and rapid convergence
lower bound	A Study on the Block Relocation Problem: Lower Bound Derivations and Strong Formulations
M
M-natural-convexity	M-natural-convexity and its applications in operations
machine cell formation	Solving Multi-Objective Combinatorial Cell Formation Problem: A Two-Step Approach Using A Distance Function and A Genetic Algorithm
machine learning	Learning-Enhanced Integer Programming: A Hybrid Approach for Routinely Solved Discrete Optimization Boolean Decision Rules via Column Generation In memory of Dave Shanno: from optimization to machine learning, it’s all the same data Learning to optimize with hidden constraints Precision Heparin Dosing using Mixed Integer Optimization Powerful Operator Splitting with Projective Splitting Surrogate Optimization of Deep Neural Networks for Groundwater Predictions Benders Cut Classification via Support Vector Machines for Solving Two-stage Stochastic Programs
Makespan	Bi-Objective Firefly Optimization Algorithm for n-Stage Parallel Machine Scheduling
Market Baskets	In memory of Dave Shanno: from optimization to machine learning, it’s all the same data
Markov decision process	Dynamic Tuberculosis Screening for Healthcare Employees Learning Interpretable Policies for Markov Decision Process by Hybrid Linear-Black-Box Model Inverse Markov decision process with unknown transition probabilities
mathematical modeling	New Multi-Step Conjugate Gradient Method for Optimization
matrix completion	Implicit Regularization in Nonconvex Statistical Estimation: Gradient Descent Converges Linearly for Phase Retrieval, Matrix Completion, and Blind Deconvolution
matrix decomposition	On SDP formulations for quadratic optimization with indicator variables
maximum entropy sampling problem	Approximation Algorithms for the Maximum Entropy Sampling Problem
MCP	Provable Generalizability of Deep Neural Networks under Sparsity-Inducing Regularization
meta learning	Meta Dynamic Pricing: Learning Across Experiments
Min-max optimization	Learning Interpretable Policies for Markov Decision Process by Hybrid Linear-Black-Box Model
MINLP	An MINLP approach to bounding probability with applications to Network routing
mirror descent	The Role of Optimization Algorithms in Generalization of Deep Learning
Mixed Integer Linear Program (MILP)	Developing a Mixed Integer Linear Program (MILP) to maximize material utilization and switch the setup from internal to external
mixed integer optimization	Precision Heparin Dosing using Mixed Integer Optimization
mixed integer program	A Study on the Block Relocation Problem: Lower Bound Derivations and Strong Formulations
Mixed Integer Programming	The RIP Technique for Box Configuration for Birchbox Learning Sparse Classifiers: Continuous and Mixed Integer Optimization Perspectives Sparse Regression with Interactions: A Scalable Integer Programming Approach
Mixed integer quadratic programs	Spectral relaxations and branching for MIQPs
Mixed integer quadratically constrained programming	Optimal location of last-mile consolidation areas to reduce environmental impact of urban deliveries of goods: a heuristic approach
Mixed-integer conic quadratic optimization	Outlier detection in time series via mixed-integer conic quadratic optimization
Mixed-Integer Convex Optimization	Disjunctive cuts for Mixed-Integer Conic Optimization
Mixed-Integer Linear Programming	Lossless Compression of Deep Neural Networks Learning-Enhanced Integer Programming: A Hybrid Approach for Routinely Solved Discrete Optimization Scenario grouping and decomposition algorithms for chance-constrained programs
Mixed-integer non-linear and linear	A distributionally robust optimization approach for outpatient colonoscopy scheduling
Mixed-integer Nonlinear Programming	Volumetric Analysis of Perspective Reformulations Sample Average Approximation for Stochastic Nonconvex Mixed Integer Nonlinear Programming via Outer Approximation
Mixed-integer optimization	Inverse Mixed-Integer Optimization with Trust-Region Methods Strong formulations for sparse regression A Unified Approach to Mixed-Integer Optimization: Nonlinear Formulations and Scalable Algorithms Sparse PCA under a conic optimization lens: MISDP reformulations and scalable SOCP bounds Subadditive Duality for Conic Mixed-Integer Programs
Mixed-integer programming	Strong mixed-integer programming formulations for trained neural networks A Distributionally Robust Optimization Approach for Stochastic Elective Surgery Scheduling with Limited ICU Capacity Estimating Wireless Mesh Network Vulnerability: A Search for the “Best” Interference Model
Mixed-integer quadratic optimization	On SDP formulations for quadratic optimization with indicator variables
Mixed-integer recourse	Solving risk-averse mixed-integer stochastic programs using convex approximations
Mixing	Cardinality Constrained Multilinear Sets
Mixing inequalities	Joint chance-constrained programs and the intersection of mixing sets through a submodularity lens
Mixing sets	Joint chance-constrained programs and the intersection of mixing sets through a submodularity lens
model-agnostic meta-learning	Biased Stochastic Approximation for Conditional Stochastic Optimization
model-free	Comparing model-free and model-based methods for multistage stochastic programming
multi-capacitated lot-sizing	Exact Algorithms for Lot-Sizing Problems with Multiple Capacities, Piecewise Concave Production Costs, and Subcontracting
Multi-scale Capacity Expansion	Distributed Algorithms for Multi-Scale Capacity Expansion Problems in Power Systems
Multi-stage parallel machines	Bi-Objective Firefly Optimization Algorithm for n-Stage Parallel Machine Scheduling
Multi-stage stochastic mixed integer programming	Optimal Crashing of an Activity Network with Multiple Disruptions
multi-stage stochastic program	Optimal Power Flow in Distribution Networks under Stochastic N-1 Disruptions
multi-stage stochastic programming	Distributionally Robust Stochastic Dual Dynamic Programming
multi-step methods	New Multi-Step Conjugate Gradient Method for Optimization
Multilevel Algorithms	Partition Hypergraphs with Embeddings
Multilinear functions	Cardinality Constrained Multilinear Sets
Multinomial Logit Choice Model	Robust Assortment Optimization under Product Unavailability
multinomial logit model	Optimizing Revenue while Showing Relevant Recommendations
multiobjective discrete optimization	Network Models for Multiobjective Discrete Optimization
Multiobjective optimization	Wasserstein Distributionally Robust Inverse Multiobjective Optimization
Multiple Optimal Solutions	Exploiting Multiple Optimal Solutions in Independent Set
multistage	Partially observable multistage stochastic programming
Multistage stochastic linear programs·	Adaptive Partition-based Stochastic Dual Dynamic Programming Algorithms For Multistage Stochastic Linear Programs
multistage stochastic programming	Stochastic Dynamic Linear Programming and its Application Comparing model-free and model-based methods for multistage stochastic programming Subtree Decomposition Method For Multistage Stochastic Programs
multistart optimization	Multistart Methods for Quantum Approximate Optimization
N
N-1 contingency	Optimal Power Flow in Distribution Networks under Stochastic N-1 Disruptions
Natural Gas Pipelines	A Reserve Scheduling Framework for Uncertainty Management in Power Systems and Gas Pipelines
Near-optimal	Near-Optimal Algorithms for Smooth Convex-Concave Minimax Optimization and Beyond
Nearest neighbors	Optimizing Revenue while Showing Relevant Recommendations
Nesting Program	Developing a Mixed Integer Linear Program (MILP) to maximize material utilization and switch the setup from internal to external
network alignment	Network Alignment by Propagating Reliable Similarities
network centrality	Centralities for Networks with Consumable Resources
Network Design	A Unified Approach to Mixed-Integer Optimization: Nonlinear Formulations and Scalable Algorithms A Stochastic Programming Model with Endogenous and Exogenous Uncertainty for Reliable Network Design Under Random Disruption
Network interdiction	A Progressive approximation approach for the exact solution of sparse large-scale binary interdiction games
network models	Network Models for Multiobjective Discrete Optimization
network robustness	Centralities for Networks with Consumable Resources
Network routing under uncertain link failures	An MINLP approach to bounding probability with applications to Network routing
network-based model	Adaptive Approximate Linear Programs based on Index Networks for Solving Weakly-coupled Dynamic Programs
network-simplex-based heuristic	Extreme-point Tabu Search Heuristic for Fixed-Charge Generalized Transshipment Problems
Networks	A Dual Approach for Optimal Algorithms in Distributed Optimization over Networks Global Supply Chain Networks and Tariff Rate Quotas: Equilibrium Analysis with Application to Agricultural Products On parametric decision diagrams
Neural Network Pruning	Lossless Compression of Deep Neural Networks
Neural networks	Convergent variants of gradient descent for neural networks Machine Learning to Address Hospital Capacity: Predicting Discharges and Identifying Barriers to Discharge On the Benefit of Width for Neural Networks: Disappearance of Basins Neural network approximations in quadratic optimization Nonlinear Regularization for Neural Networks
Neuron Stability	Lossless Compression of Deep Neural Networks
newborn screening	Equity in Genetic Newborn Screening
Newton Method	Zeroth-order Nonconvex Stochastic Optimization: Handling Constraints, High-Dimensionality, and Saddle-Points
Noisy binary search	Optimizing Revenue while Showing Relevant Recommendations
non-convex	Convergent variants of gradient descent for neural networks
Non-convex optimization	Scaling Up Quasi-Newton Algorithms: Communication Efficient Distributed SR1 Strong contraction mapping and topological non-convex optimization
non-stationary online optimization	Reinforcement Learning under Drift: The Blessing of (More) Optimism
Nonconvex	Radial Duality
nonconvex optimization	Bridging Convex and Nonconvex Optimization in Robust PCA: Noise, Outliers, and Missing Data Implicit Regularization in Nonconvex Statistical Estimation: Gradient Descent Converges Linearly for Phase Retrieval, Matrix Completion, and Blind Deconvolution A Line-Search Descent Algorithm for Strict Saddle Functions with Complexity Guarantees New Bregman proximal type algorithms for solving DC optimization problems Structured local minima in some nonconvex optimization problems Near-optimal bounds for phase synchronization
Nonconvex optimization with nonlinear equality constraints	Complexity of proximal augmented Lagrangian for nonconvex optimization with nonlinear equality constraints
Nonconvex Stochastic Optimization	Zeroth-order Nonconvex Stochastic Optimization: Handling Constraints, High-Dimensionality, and Saddle-Points
Nonconvex-concave	Near-Optimal Algorithms for Smooth Convex-Concave Minimax Optimization and Beyond
nonincreasing optimal solution	M-natural-convexity and its applications in operations
Nonlinear Optimization	Scaling Up Quasi-Newton Algorithms: Communication Efficient Distributed SR1 A Heuristic and Exact Solution Approach for the 0-1 Cubic Knapsack Problem
Nonlinear Programming	Reflections on Dave Shanno Remembering Dave Shanno: Twenty Years of Collaboration In Memory of Dave Shanno: making an interior-point method for NLP converge In memory of Dave Shanno: Revisiting Quasi-Newton Methods Solving the Problem of Portfolio VAR Minimization as a Nonlinear Program
nonlinear stochastic model	Incentivizing Homeowners for Tree Management using a Principal-Agent Game-Theoretical Approach
NonLipschitz	Radial Duality
Nonsmooth optimization	Low-rank matrix recovery with composite optimization: good conditioning and rapid convergence Nonsmooth Optimization over Stiefel Manifold: Riemannian Subgradient Methods
Nonsymmetric cones	Hypatia: Generic Nonsymmetric Conic Optimization in Julia
Nurse staffing	Nurse Staffing under Absenteeism: A Distributionally Robust Optimization Approach
Nutrient reduction	A stochastic mixed integer linear program for agricultural land use optimization
O
observational data	Safely Learning to Personalize from Sequential Observational Data
ODEs	An $O(s^r)$-Resolution ODE Framework for Discrete-Time Optimization Algorithms and Applications to Convex-Concave Saddle-Point Problems
One-step Look-ahead Policy	Personalized Dose Finding Trials
Online algorithms	Dynamic Resource Allocation in the Cloud with Near-Optimal Efficiency
online and approximation algorithms	The Competitive Ratio of Threshold Policies for Online Unit-density Knapsack Problems
Online convex optimization	Online Primal-Dual Mirror Descent under Stochastic Constraints
online hiring	Impact of Bias on Hiring Decisions
Online learning	Online Learning in Service Systems: Optimal Pricing And Capacity Sizing For A G/G/1 Queue With Demand Learning
online optimization	A Model of the Online Independent Set Problem
open source software	Advances in Scalable Open Source Software for Parallel Stochastic Programming
operating room scheduling	Improving Operating Room Scheduling: Integer and Constraint Programming Approaches
OPF	Optimal Power Flow in Distribution Networks under Stochastic N-1 Disruptions
optimal algorithms	A Dual Approach for Optimal Algorithms in Distributed Optimization over Networks
Optimal Decision Tree	Optimal Decision Tree with Noisy Outcomes
Optimal power	Integrated Learning and Optimization for AC-OPF
Optimal Scheduling	A Reserve Scheduling Framework for Uncertainty Management in Power Systems and Gas Pipelines
optimal transport	A Dual Approach for Optimal Algorithms in Distributed Optimization over Networks
optimization	Convergent variants of gradient descent for neural networks Safely Learning to Personalize from Sequential Observational Data Causal Inference with Selectively-Deconfounded Data Risk Guarantees For End-to-end Prediction and Optimization Processes Integrated Learning and Optimization for AC-OPF Variance Reduction in Stochastic Programming and Applications in Logistics
Optimization on manifolds	Coordinate Descent Without Coordinates: Tangent Subspace Descent on Riemannian Manifolds
Optimization under uncertainty	Optimal Decision Tree with Noisy Outcomes
OR for Social Good	Exploring Algorithmic Fairness in Robust Graph Covering Problems
OR in health services	A distributionally robust optimization approach for outpatient colonoscopy scheduling
order statistics	Robust Optimization with Order Statistic Uncertainty Set
orienteering	A Team Orienteering Problem for Fixed-Wing Drones
Outer Approximation	Sample Average Approximation for Stochastic Nonconvex Mixed Integer Nonlinear Programming via Outer Approximation A Unified Approach to Mixed-Integer Optimization: Nonlinear Formulations and Scalable Algorithms
Outlier robust	Composite optimization for blind deconvolution
over-parameterization	Provable Generalizability of Deep Neural Networks under Sparsity-Inducing Regularization On the Benefit of Width for Neural Networks: Disappearance of Basins
P
panel design	Equity in Genetic Newborn Screening
parallel computing	Data driven stochastic optimization applied to renewable energy penetration in power systems Advances in Scalable Open Source Software for Parallel Stochastic Programming
Parameter fitting	Engineering fast multilevel support vector machines
Parametric Optimization	An Algorithm for Parametric Quadratically Constrained Quadratic Programs
partial convex hull	(Partial) Convex Hull for Deterministic and Stochastic Structured Conic Mixed Integer Sets using Conic Mixed Integer Rounding
partially observable	Partially observable multistage stochastic programming
Personalized Day Tour	Maximizing the total pleasure from a personalized day tour
Personalized Medicine	Personalized Dose Finding Trials
Perspective formulation	On SDP formulations for quadratic optimization with indicator variables On the convexification of constrained quadratic optimization problems with indicator variables
perspective reformulation	Volumetric Analysis of Perspective Reformulations
pharmaceutical	Adaptive Pharmaceutical Supply Chain Design under Disruption and its Effects on Drug Shortages
Phase transition	On the Benefit of Width for Neural Networks: Disappearance of Basins
piecewise concave production cost	Exact Algorithms for Lot-Sizing Problems with Multiple Capacities, Piecewise Concave Production Costs, and Subcontracting
polyhedral study	A Model of the Online Independent Set Problem
Polyhedral Theory	Ranking-based Facet Defining Inequalities for the Weak Order Polytope
Polymatroid inequalities	Joint chance-constrained programs and the intersection of mixing sets through a submodularity lens
Polynomial Optimization	On Local Minima of Cubic Polynomials
polytope	Volumetric Analysis of Perspective Reformulations
positive-valued function	Learning Positive-Valued Functions with Pseudo Mirror Descent
Posterior Sampling	Personalized Dose Finding Trials
Power Grid	A Reserve Scheduling Framework for Uncertainty Management in Power Systems and Gas Pipelines
power method	Near-optimal bounds for phase synchronization
Power Systems	Data driven stochastic optimization applied to renewable energy penetration in power systems Path-based Valid Inequalities for DC Power Systems with Discrete Transmission Considerations
Preconditioning	Acceleration of Primal-Dual Methods by Preconditioning and Simple Subproblem Procedures
prediction	Risk Guarantees For End-to-end Prediction and Optimization Processes
Predictive modeling	JANOS : An Integrated Predictive and Prescriptive Modeling Framework A Stochastic Programming Model with Endogenous and Exogenous Uncertainty for Reliable Network Design Under Random Disruption
predictive-and-prescriptive analytics	Data-Driven Optimization for Team Formation
preference elicitation	Robust Optimization with Decision-Dependent Information Discovery Optimal Active Preference Elicitation via Adjustable Robust Optimization
prescriptive analysis	JANOS : An Integrated Predictive and Prescriptive Modeling Framework
price of equity	Equity in Genetic Newborn Screening
Primal-Dual Hybrid Gradient	Acceleration of Primal-Dual Methods by Preconditioning and Simple Subproblem Procedures
principal-agent framework	Incentivizing Homeowners for Tree Management using a Principal-Agent Game-Theoretical Approach
product transition	A bilevel programming model for coordinating product transitions
Product Trasitions	An Integer Column Generation Procedure for Coordinating Product Transitions in Semiconductor Manufacturing using Combinatorial Auctions
production planning	Exact Algorithms for Lot-Sizing Problems with Multiple Capacities, Piecewise Concave Production Costs, and Subcontracting
programming	A distributionally robust optimization approach for outpatient colonoscopy scheduling
project buffers	Earned Value Measurement in Project Buffers Management
project control	Earned Value Measurement in Project Buffers Management
Project crashing	Optimal Crashing of an Activity Network with Multiple Disruptions
project management	Earned Value Measurement in Project Buffers Management
Projection-Free	Radial Duality
Protein-Protein Interaction Networks	The Star Degree Centrality Problem: A Benders Decomposition Approach
Proximal augmented Lagrangian	Complexity of proximal augmented Lagrangian for nonconvex optimization with nonlinear equality constraints
proximal operator splitting	Powerful Operator Splitting with Projective Splitting
Proximal point algorithm	New Bregman proximal type algorithms for solving DC optimization problems
pseudo gradient	Learning Positive-Valued Functions with Pseudo Mirror Descent
Q
Q-learning	Lookahead-bounded Q-learning
QCQP	Neural network approximations in quadratic optimization
quadratic assignment problem	Characterizing Linearizable QAPs by the Level-1 RLT Network Alignment by Propagating Reliable Similarities
Quadratic optimization	On the convexification of constrained quadratic optimization problems with indicator variables
Quadratic Unconstrained Binary Optimization	Template-based Minor Embedding for Adiabatic Quantum Optimization The Potential of Quantum Annealing for Rapid Solution Structure Identification
Quadratically constrained quadratic programming	On the tightness of SDP relaxations of QCQPs
quantile bounds	Scenario grouping and decomposition algorithms for chance-constrained programs
Quantum Annealers	Integer programming techniques for minor-embedding in quantum annealers
Quantum Annealing	The Potential of Quantum Annealing for Rapid Solution Structure Identification
quantum approximate optimization	Multistart Methods for Quantum Approximate Optimization
quasi-Newton Methods	In memory of Dave Shanno: Revisiting Quasi-Newton Methods New Multi-Step Conjugate Gradient Method for Optimization
R
Random features	Self-guided Approximate Linear Programs
Random Fourier features	Self-guided Approximate Linear Programs
random no-shows	Data-Driven Distributionally Robust Appointment Scheduling
random-walk betweenness centrality	Centralities for Networks with Consumable Resources
Randomized rounding	A Unified Approach to Mixed-Integer Optimization: Nonlinear Formulations and Scalable Algorithms
Rank one	On Sufficient and Necessary Conditions for Rank-One Generated Cones
Ranking Aggregation	Ranking-based Facet Defining Inequalities for the Weak Order Polytope
Ranking-based Choice Model	Robust Assortment Optimization under Product Unavailability
rare events	Data-Driven Two-Stage Conic Optimization with Rare High-Impact Zero-One Uncertainties
recommendations	Optimizing Revenue while Showing Relevant Recommendations
recommender system	Optimal Active Preference Elicitation via Adjustable Robust Optimization
recovery	Optimal Power Flow in Distribution Networks under Stochastic N-1 Disruptions
Rectifier Linear Unit	Lossless Compression of Deep Neural Networks
Regression	Data-driven sample average approximation with covariate information Sparse Regression with Interactions: A Scalable Integer Programming Approach A mixed-integer optimization approach for exhaustive cross-validated model selection
regularized cutting plane methods	Stochastic Dynamic Linear Programming and its Application
reinforcement learning	Self-guided Approximate Linear Programs Reinforcement Learning under Drift: The Blessing of (More) Optimism
relaxation	Volumetric Analysis of Perspective Reformulations
Renewable energy	Data driven stochastic optimization applied to renewable energy penetration in power systems Spatio-temporal forecasting for wind energy and its impact on wind farm operations Stochastic DC Optimal Power Flow With Reserve Saturation
Resource allocation	Dynamic Resource Allocation in the Cloud with Near-Optimal Efficiency
Riemannian subgradient method	Nonsmooth Optimization over Stiefel Manifold: Riemannian Subgradient Methods
risk	Risk Guarantees For End-to-end Prediction and Optimization Processes
risk-averse decision making	Mean-Risk Two-Stage Vaccine Allocation Under Uncertainty
Risk-aversion	Solving risk-averse mixed-integer stochastic programs using convex approximations
RLT	Characterizing Linearizable QAPs by the Level-1 RLT
Robust MDP	Data-Driven Robust MDPs Using Distance-Based Ambiguity Sets
robust optimization	Exploring Algorithmic Fairness in Robust Graph Covering Problems Optimization Under Uncertainty in Kidney Exchange Robust Optimization with Decision-Dependent Information Discovery Optimal Active Preference Elicitation via Adjustable Robust Optimization Robust Assortment Optimization under Product Unavailability Robust Optimization with Order Statistic Uncertainty Set An MINLP approach to bounding probability with applications to Network routing On parametric decision diagrams
robust principal component analysis	Bridging Convex and Nonconvex Optimization in Robust PCA: Noise, Outliers, and Missing Data
robustness to unobservables	Safely Learning to Personalize from Sequential Observational Data
Rolling-horizon procedure	Adaptive Partition-based Stochastic Dual Dynamic Programming Algorithms For Multistage Stochastic Linear Programs
S
S-convexity	M-natural-convexity and its applications in operations
Saddle-point problems	An $O(s^r)$-Resolution ODE Framework for Discrete-Time Optimization Algorithms and Applications to Convex-Concave Saddle-Point Problems
sample average approximation	Sample Complexity of Sample Average Approximation for Conditional Stochastic Optimization Data-driven sample average approximation with covariate information Sample Average Approximation for Stochastic Nonconvex Mixed Integer Nonlinear Programming via Outer Approximation
Sample Complexity	Causal Inference with Selectively-Deconfounded Data
sampling algorithm	Approximation Algorithms for the Maximum Entropy Sampling Problem
SCAD	Provable Generalizability of Deep Neural Networks under Sparsity-Inducing Regularization
scenario decomposition	Advances in Scalable Open Source Software for Parallel Stochastic Programming Scenario grouping and decomposition algorithms for chance-constrained programs
Scenario reduction	Using Effective Scenarios to Accelerate Decomposition Algorithms for Two-stage Distributionally Robust Optimization with Total Variation Distance
scenario tree decomposition	Subtree Decomposition Method For Multistage Stochastic Programs
scenario-based cuts	(Partial) Convex Hull for Deterministic and Stochastic Structured Conic Mixed Integer Sets using Conic Mixed Integer Rounding
SDDP	Comparing model-free and model-based methods for multistage stochastic programming
SDDP algorithm	Adaptive Partition-based Stochastic Dual Dynamic Programming Algorithms For Multistage Stochastic Linear Programs
SDDP.jl	Bi-objective multistage stochastic linear programming
Second order cone programming	Conic Formulations for a Mean-Risk Stochastic Mixed Integer Nonlinear Program with Applications to Network Protection
Second-order cone optimization	Sparse PCA under a conic optimization lens: MISDP reformulations and scalable SOCP bounds
secretary problem	Impact of Bias on Hiring Decisions
Semiconductor Manufacturing	An Integer Column Generation Procedure for Coordinating Product Transitions in Semiconductor Manufacturing using Combinatorial Auctions
Semidefinite optimization	Sparse PCA under a conic optimization lens: MISDP reformulations and scalable SOCP bounds
Semidefinite program	On Sufficient and Necessary Conditions for Rank-One Generated Cones On the tightness of SDP relaxations of QCQPs
semidefinite programming	Learning Dynamical Systems with Side Information On SDP formulations for quadratic optimization with indicator variables Weak infeasibility in semidefinite programming: a complete characterization and generating all instances Computing the Projection onto the Degenerate Doubly Nonnegative Cone On Local Minima of Cubic Polynomials Near-optimal bounds for phase synchronization
semismooth Newton method	Computing the Projection onto the Degenerate Doubly Nonnegative Cone
Sensitivity	Solving Multi-Objective Combinatorial Cell Formation Problem: A Two-Step Approach Using A Distance Function and A Genetic Algorithm
sensitivity analysis	Safely Learning to Personalize from Sequential Observational Data
Sequential optimization	A Progressive approximation approach for the exact solution of sparse large-scale binary interdiction games
sequential sampling	A Sequential Sampling Method for Distributionally Robust Linear Programs Stochastic Dynamic Linear Programming and its Application
set packing	Optimization Under Uncertainty in Kidney Exchange
set-covering problem	Minimum blockers for the set covering problem
simulation-optimization	Tutorial: A Unified Framework for Sequential Decisions under Uncertainty
Sliding	Sliding Linearized ADMM For Convex Smooth Optimization With Affine Constraints
Software	Dualization and Bilevel optimization in JuMP
solver	JANOS : An Integrated Predictive and Prescriptive Modeling Framework
solving quadratic systems of equations	Implicit Regularization in Nonconvex Statistical Estimation: Gradient Descent Converges Linearly for Phase Retrieval, Matrix Completion, and Blind Deconvolution
spanning trees	Electrical Flows over Spanning Trees
Sparse PCA	Sparse PCA under a conic optimization lens: MISDP reformulations and scalable SOCP bounds
sparse regression	Strong formulations for sparse regression
Sparsity	Learning Sparse Classifiers: Continuous and Mixed Integer Optimization Perspectives Sparse Regression with Interactions: A Scalable Integer Programming Approach
Spatial branch-and-cut	Optimal Crashing of an Activity Network with Multiple Disruptions
spatial statistics	Aspects of maximum-entropy sampling
Spatio-temporal random fields	Data-driven optimization for wind farm siting
Spectral initialization	Composite optimization for blind deconvolution
stable set	A Model of the Online Independent Set Problem
Star Degree Centrality	The Star Degree Centrality Problem: A Benders Decomposition Approach
steel slab	A Study on the Block Relocation Problem: Lower Bound Derivations and Strong Formulations
Stefiel manifold	Nonsmooth Optimization over Stiefel Manifold: Riemannian Subgradient Methods
Stein’s identity	Zeroth-order Nonconvex Stochastic Optimization: Handling Constraints, High-Dimensionality, and Saddle-Points
Stochastic approximation	Katyusha Acceleration for Convex Finite-Sum Compositional Optimization Stochastic DC Optimal Power Flow With Reserve Saturation
stochastic decomposition	Stochastic Dynamic Linear Programming and its Application
stochastic disruption	Optimal Power Flow in Distribution Networks under Stochastic N-1 Disruptions
Stochastic disruptions	Optimal Crashing of an Activity Network with Multiple Disruptions
stochastic dual dynamic programming	Partially observable multistage stochastic programming Distributionally Robust Stochastic Dual Dynamic Programming Bi-objective multistage stochastic linear programming
Stochastic Dynamic Dual Programming	A Data-Driven Approach for a Class of Stochastic Dynamic Optimization Problems
stochastic gradient descent	The Role of Optimization Algorithms in Generalization of Deep Learning Convergent variants of gradient descent for neural networks Online Learning in Service Systems: Optimal Pricing And Capacity Sizing For A G/G/1 Queue With Demand Learning
Stochastic Gradient Methods	A Data Efficient and Feasible Level Set Method for Stochastic Convex Optimization with Expectation Constraints
stochastic integer programming	Stochastic Team Formation Problem On the Values of Vehicle-to-Grid Electricity Selling in Electric Vehicle Sharing
stochastic mirror descent	Learning Positive-Valued Functions with Pseudo Mirror Descent
Stochastic mixed-integer linear program	A stochastic mixed integer linear program for agricultural land use optimization
Stochastic Modeling	Spatio-temporal forecasting for wind energy and its impact on wind farm operations
Stochastic optimal power flow	Stochastic DC Optimal Power Flow With Reserve Saturation
stochastic optimization	Complexity of stochastic dual dynamic programming Optimization Under Uncertainty in Kidney Exchange Sample Complexity of Sample Average Approximation for Conditional Stochastic Optimization Biased Stochastic Approximation for Conditional Stochastic Optimization Tutorial: A Unified Framework for Sequential Decisions under Uncertainty
Stochastic optimization·	Adaptive Partition-based Stochastic Dual Dynamic Programming Algorithms For Multistage Stochastic Linear Programs
stochastic programmin	Coupled Learning Enabled Stochastic Programming with Endogenous Uncertainty
stochastic programming	Solving risk-averse mixed-integer stochastic programs using convex approximations Data driven stochastic optimization applied to renewable energy penetration in power systems Advances in Scalable Open Source Software for Parallel Stochastic Programming Partially observable multistage stochastic programming Adaptive Pharmaceutical Supply Chain Design under Disruption and its Effects on Drug Shortages Joint chance-constrained programs and the intersection of mixing sets through a submodularity lens Mean-Risk Two-Stage Vaccine Allocation Under Uncertainty Sample Average Approximation for Stochastic Nonconvex Mixed Integer Nonlinear Programming via Outer Approximation Bi-objective multistage stochastic linear programming Tutorial: A Unified Framework for Sequential Decisions under Uncertainty A Stochastic Programming Model with Endogenous and Exogenous Uncertainty for Reliable Network Design Under Random Disruption Distributed Algorithms for Multi-Scale Capacity Expansion Problems in Power Systems
strict saddle	A Line-Search Descent Algorithm for Strict Saddle Functions with Complexity Guarantees
Structured subproblem	Acceleration of Primal-Dual Methods by Preconditioning and Simple Subproblem Procedures
Subadditive Duality	An Integer Column Generation Procedure for Coordinating Product Transitions in Semiconductor Manufacturing using Combinatorial Auctions
Subgradient Optimization	An Algorithm for Parametric Quadratically Constrained Quadratic Programs
Submodular function	Joint chance-constrained programs and the intersection of mixing sets through a submodularity lens
submodular optimization	Categorical Feature Compression via Submodular Optimization
Substitutability	M-natural-convexity and its applications in operations
Sum of Squares	On Local Minima of Cubic Polynomials
Sum of Squares Optimization	Learning Dynamical Systems with Side Information
superlinear convergence	Computing the Projection onto the Degenerate Doubly Nonnegative Cone
Supply chains	Global Supply Chain Networks and Tariff Rate Quotas: Equilibrium Analysis with Application to Agricultural Products
Support vector machine	Engineering fast multilevel support vector machines
Support Vector Machines	Benders Cut Classification via Support Vector Machines for Solving Two-stage Stochastic Programs
Surgery Scheduling	A Distributionally Robust Optimization Approach for Stochastic Elective Surgery Scheduling with Limited ICU Capacity
Surrogate models	Surrogate Optimization of Deep Neural Networks for Groundwater Predictions
sustainable transportation	On the Values of Vehicle-to-Grid Electricity Selling in Electric Vehicle Sharing
Symmetry	Exploiting symmetry in linear programming Exploiting almost identical generators in unit commitment
T
Tariff rate quotas	Global Supply Chain Networks and Tariff Rate Quotas: Equilibrium Analysis with Application to Agricultural Products
teaching assignment	University timetabling problem with requested instructor workload using constraint program
Team formation	Stochastic Team Formation Problem Data-Driven Optimization for Team Formation
Thompson sampling	Meta Dynamic Pricing: Learning Across Experiments
Tolerance solution	Control and tolerance two-sided interval linear programming problems
Total flow time	Bi-Objective Firefly Optimization Algorithm for n-Stage Parallel Machine Scheduling
Tractability	Tractable Reformulations of Distributionally Robust Two-stage Stochastic Programs with $\infty-$Wasserstein Distance
transfer learning	Meta Dynamic Pricing: Learning Across Experiments
Transmission Expansion Planning	Path-based Valid Inequalities for DC Power Systems with Discrete Transmission Considerations
Transmission grid operation	Distributionally Robust Transmission Grid under Geomagnetic Disturbances
Transmission Switching	Path-based Valid Inequalities for DC Power Systems with Discrete Transmission Considerations
Trust-Region Methods	Inverse Mixed-Integer Optimization with Trust-Region Methods
Tuberculosis infection	Dynamic Tuberculosis Screening for Healthcare Employees
Tuberculosis screening	Dynamic Tuberculosis Screening for Healthcare Employees
two-stage distributionally robust conic mixed integer program	(Partial) Convex Hull for Deterministic and Stochastic Structured Conic Mixed Integer Sets using Conic Mixed Integer Rounding
two-stage problems	Data-Driven Two-Stage Conic Optimization with Rare High-Impact Zero-One Uncertainties Robust Optimization with Decision-Dependent Information Discovery
two-stage stochastic programming	A Decomposition Interior-Point Algorithm for Stochastic Linear Optimization in a Hilbert Space Benders Cut Classification via Support Vector Machines for Solving Two-stage Stochastic Programs
U
UAV	Robust two echelon vehicle and drone routing for humanitarian relief operations
ultrasound/MRI	Data-driven optimization of supplemental screening usage in breast cancer detection
Uncertainty	Last mile scheduling under uncertainty Network Interdiction with Asymmetric Cost Uncertainty Variance Reduction in Stochastic Programming and Applications in Logistics
Uncertainty Quantification	An MINLP approach to bounding probability with applications to Network routing A Reserve Scheduling Framework for Uncertainty Management in Power Systems and Gas Pipelines
uncertainty set	Robust Optimization with Order Statistic Uncertainty Set
unconstrained optimization	New Multi-Step Conjugate Gradient Method for Optimization
Unit Commitment	Exploiting almost identical generators in unit commitment
Utility Theory	Maximizing the total pleasure from a personalized day tour
V
vaccine allocation	Mean-Risk Two-Stage Vaccine Allocation Under Uncertainty
Valid inequalities	Cardinality Constrained Multilinear Sets On Polyhedra of Two Influence Maximization Problems in Social Networks Path-based Valid Inequalities for DC Power Systems with Discrete Transmission Considerations
valid inequality	On SDP formulations for quadratic optimization with indicator variables
value of supplemental testing	Data-driven optimization of supplemental screening usage in breast cancer detection
VAR	Solving the Problem of Portfolio VAR Minimization as a Nonlinear Program
Variable selection	A mixed-integer optimization approach for exhaustive cross-validated model selection
variance reduction	Katyusha Acceleration for Convex Finite-Sum Compositional Optimization
Variational inequalities	Global Supply Chain Networks and Tariff Rate Quotas: Equilibrium Analysis with Application to Agricultural Products
Variational regularization	Nonlinear Regularization for Neural Networks
vehicle routing	Robust two echelon vehicle and drone routing for humanitarian relief operations A multi-vehicle covering tour problem with speed optimization
vehicle-to-grid (V2G)	On the Values of Vehicle-to-Grid Electricity Selling in Electric Vehicle Sharing
Vertex Solution	Exploiting symmetry in linear programming
vocabulary compression	Categorical Feature Compression via Submodular Optimization
volume	Volumetric Analysis of Perspective Reformulations
W
Warm Starts	Learning-Enhanced Integer Programming: A Hybrid Approach for Routinely Solved Discrete Optimization
Wasserstein barycenters	A Dual Approach for Optimal Algorithms in Distributed Optimization over Networks
Wasserstein metric	Data-Driven Robust MDPs Using Distance-Based Ambiguity Sets
weak infeasibility	Weak infeasibility in semidefinite programming: a complete characterization and generating all instances
Weakly convex	Nonsmooth Optimization over Stiefel Manifold: Riemannian Subgradient Methods
Wind farm	Data-driven optimization for wind farm siting
Wind power output	Data-driven optimization for wind farm siting
Wireless network jamming	Estimating Wireless Mesh Network Vulnerability: A Search for the “Best” Interference Model
worst-case efficiency estimates	Understanding Limitation of Two Symmetrized Orders by Worst-case Complexity
Z
Zero-one Mixed Integer Programming	Maximizing the total pleasure from a personalized day tour
Zeroth-order methods	Zeroth-order Nonconvex Stochastic Optimization: Handling Constraints, High-Dimensionality, and Saddle-Points

Disclaimer | Powered by EasyChair Smart Program