A Hybrid Heuristic Optimization Approach for Green Flatcar Transportation Scheduling in Shipbuilding

EasyChair Preprint 3676

Abstract

To increase efficiency and decrease energy in fierce competition, higher standard of transportation scheduling mode for shipbuilding is necessary and urgent. By analyzing the “one-vehicle and one-cargo” transportation scheduling problem in shipbuilding, this paper proposes a bi-objective mathematical model and design a Multi-Objective Tabu Search algorithm(MOTS) to minimize total carbon emission and transportation time cost. Further, to improve the computation performance of the solution method, we combined NSGA-Ⅱ and MOTS to design a hybrid heuristic algorithm. Computational experiments compare three optimizing approaches and reveal that MOTS and NSGAⅡ-MOTS have certain advantages in terms of solution effect and convergence speed in large-scale instances. The case shows the proposed optimization approach can reduce carbon emissions by 61.22% for daily transportation.

Keyphrases: Muti-objective optimization, green transportation scheduling, hybrid heuristic optimization, ship block transportation

@booklet{EasyChair:3676,
  author    = {Yini Chen and Zuhua Jiang and Baihe Li},
  title     = {A Hybrid Heuristic Optimization Approach for Green Flatcar Transportation Scheduling in Shipbuilding},
  howpublished = {EasyChair Preprint 3676},
  year      = {EasyChair, 2020}}