HMRA 2018: Hybrid Metaheuristics: Research and Applications |
Website | http://teamsb.net/hmra/ |
Submission link | https://easychair.org/conferences/?conf=hmra2018 |
Abstract registration deadline | July 31, 2017 |
Submission deadline | November 10, 2017 |
A metaheuristic is a higher-level procedure designed to select a heuristic (partial search algorithm) that may lead to a sufficiently good solution to an optimization problem, especially with incomplete or imperfect information. The basic principle of metaheuristics is to sample a set of solutions which is large enough to be completely sampled. As metaheuristics make few assumptions about the optimization problem to be solved, they may be put to use in a variety of problems. Metaheuristics do not however, guarantee that a globally optimal solution can be found on some class of problems since most of them implement some form of stochastic optimization. Hence the solution found is often dependent on the set of random variables generated. By searching over a large set of feasible solutions, metaheuristics can often find good solutions with less computational effort than optimization algorithms, iterative methods, or simple heuristics. As such, they are useful approaches for optimization problems. Even though the metaheuristics are robust enough to yield optimum solutions, yet they often suffer from time complexity and degenerate solutions. In an effort to alleviate these problems, scientists and researchers have come up with the hybridization of the different metaheuristic approaches by conjoining with other soft computing tools and techniques to yield failsafe solutions. A hybrid metaheuristic is essentially a technique that results from the combination of a metaheuristic with other techniques for optimization In a recent advancement, quantum mechanical principles are being employed to cut down the time complexity of the metaheuristic approaches to a great extent. Thus, the hybrid metaheuristic approaches have come a long way in dealing with the real life optimization problems quite successfully.
This book is intended to bring together researchers to report the latest progress in Hybrid Metaheuristics and their applications to engineering and science.
Submission Guidelines
Prospective authors are invited to submit a 3- 4 pages Abstract of the chapter along with title of the chapter and author details. Abstract should highlight the novelty and contribution of the proposed article. Authors need to submit this abstract using the Easy Chair submission link given below. Last date for Abstract submission is 31st July 2017. Once the Abstract (Chapter Proposal) is accepted then the full chapter need to be prepared using the LaTeX template given below. All submissions should be done through Easy Chair submission link given below.
1. LaTex Templates are available at http://teamsb.net/hmra/docs/wsclatex.zip
2. EasyChair submission link: https://easychair.org/conferences/?conf=hmra2018
List of Topics
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Mechanical Engineering – Production planning; scheduling and coordination; expert system design; cooperative control; dynamic system analysis; renewable energy systems; robotics and robotic vision engineering problems; process automation
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Power Control and Optimization – Power control; future energy planning and environment; industrial Informatics and planning; scheduling and assignment problems; optimization; economic load dispatch
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Total Quality Management – TQM intelligent methods; business excellence models; intelligent and virtual CMM
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Machine Intelligence – Data processing, analysis and applications; intelligent systems; emerging computing paradigms
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Nanoscience and Nanoengineering – Artificial intelligence and soft computing techniques; parallel and distributed computing; grid computing and pervasive computing; adaptive reconfigurable architectures
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Mining Engineering – Mine planning and modeling; mine safety methods using intelligent VR and HCI techniques
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Signal Processing – Algorithms, architectures and applications; multidimensional signal processing; radar signal and data processing; VLSI for network processing; embedded reconfigurable architectures; spread spectrum and CDMA systems; antennas and propagation; mobile ad hoc networking; sensor networks
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Civil Engineering – Modeling and optimization of manufacturing systems and processes; computational fluid dynamics; flood forecasting; analysis of processing of GIS, GPS, remote sensing data; automated inspection
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Computer, Communication, Networking and Information Engineering – Intelligent network management; antenna design, information security; cross-layer optimized wireless networks; pattern recognition; 2D, 3D and multidimensional image processing and analysis, target tracking, biomedical signal processing, video processing and analysis, big data analytics
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Optical Engineering – Optical computing; optical image processing; optical testing; optical communication systems and networks; intelligent photonics
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Bioinformatics and Biomedical Engineering – Bio-molecular and phylogenetic databases; Biomedical engineering; biomedical robotics and mechanics; bio-signal processing and analysis; biometrics and bio-measurements
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Ecology and Environmental Engineering – Green energy engineering; environmental pollution and remediation; environmental sustainability and restoration; hazardous substances and detection techniques; air pollution and control; solid waste management
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Engineering Management and Service Sciences – Engineering management; portfolio management; emergency management system; supply chain management; service sciences; converged network and services; e-commerce and e-governance
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Systems Engineering – Industrial automation and robotics; intelligent photonics and lighting systems; computer assisted medical diagnostic systems; unmanned aerospace systems; intelligent control systems; intelligent approaches in system identification/modeling
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Innovative Computing Systems – Intelligent manufacturing systems; quantum inspired soft computing methodologies for signal, image and information processing; medical innovative technologies
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Adaptive Technologies for Sustainable Growth – Soft computing based power systems; bio-medical engineering systems; trends and development in nano technology; wireless sensors and networks, mobile computing
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Social Networks - Text Mining, social network analysis, social network metrics, community detection, community evolution tracking, relationship networks, viral market, user influence, social influence, opinion mining, sentiment analysis
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Theoretical and Applied Sciences – Optimization and analysis of mathematical functions; statistical time series analysis; characterization of chaos theory; theory of fractals and applications to uncertainty management; applications of computational intelligence to atmospheric sciences
Editor
Prof. (Dr.) Siddhartha Bhattacharyya
Publication
The book will be published by World Scientific Publishing Co. Pte. Ltd., Singapore.
Contact
All questions about submissions should be emailed to Prof. (Dr.) Siddhartha Bhattacharyya; Email: dr.siddhartha.bhattacharyya@ieee.org