Multi-objective local search combined with NSGA-II for Bi-criteria permutation flow shop scheduling problem

作者：Wei Xin^*; Zhang Wenqiang; Weng Wei; Fujimura Shigeru

来源：IEEJ Transactions on Electronics, Information and Systems, 2012, 132(1): 32-41+3.

DOI：10.1541/ieejeiss.132.32

• Active blocks
• Bi-criteria
• Flow shop scheduling problem
• Flow-shops
• Local search
• Makespan
• Maximum tardiness
• Minimizing makespan
• Multi objective
• Multi objective evolutionary algorithms
• Multi-objective genetic algorithm
• Neighborhood structure
• Non-dominated Sorting
• NSGA-II
• Parameters setting
• Permutation flow-shop scheduling
• Search direction
• Systematic changes
• Test performance

This paper proposed a multi-objective local search procedure (MOLS). It is combined with NSGA-II for solving bi-criteria PFSP with the objectives of minimizing makespan and maximum tardiness. Utilizing the properties of active blocks for flow shop scheduling problem, neighborhood structures MOINS (multi-objective insertion) and MOEXC (multi-objective exchange) are designed in order to improve efficiency of perturbation. Any perturbation based on MOINS and MOEXC takes effect on different criteria simultaneously. The original idea of MOLS is systematic change neighborhoods in the local search procedure. The search direction of MOLS on an individual is naturally guided by interaction of MOINS and MOEXC. Moreover, there is no need to set parameters in MOLS. The MOLS combined with popular multi-objective evolutionary algorithm NSGA-II (Non-dominated Sorting Genetic Algorithm-II) is called as "NSGA-II- MOLS". To illustrate the efficacy of proposed approach, four different scaled problems are used to test performance of NSGA-II-MOLS. The numerous comparisons show efficacy of NSGA-II-MOLS is better than most of algorithms even with the same number of individual evaluations and parameters setting.

• 出版日期2012