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

Xin Wei*, Wenqiang Zhang, Wei Weng, Shigeru Fujimura

*Corresponding author for this work

Research output: Contribution to journalArticlepeer-review

6 Citations (Scopus)


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.

Original languageEnglish
Pages (from-to)32-41+3
JournalIEEJ Transactions on Electronics, Information and Systems
Issue number1
Publication statusPublished - 2012


  • Flow Shop
  • Makespan
  • Maximum Tardiness
  • Multi-objective Genetic Algorithm

ASJC Scopus subject areas

  • Electrical and Electronic Engineering


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