A research survey: heuristic approaches for solving multi objective flexible job shop problems

Turkyilmaz A., ŞENVAR Ö., Unal I., BULKAN S.

JOURNAL OF INTELLIGENT MANUFACTURING, vol.31, no.8, pp.1949-1983, 2020 (SCI-Expanded) identifier identifier

  • Publication Type: Article / Article
  • Volume: 31 Issue: 8
  • Publication Date: 2020
  • Doi Number: 10.1007/s10845-020-01547-4
  • Journal Name: JOURNAL OF INTELLIGENT MANUFACTURING
  • Journal Indexes: Science Citation Index Expanded (SCI-EXPANDED), Scopus, IBZ Online, ABI/INFORM, Applied Science & Technology Source, Business Source Elite, Business Source Premier, Compendex, Computer & Applied Sciences, INSPEC
  • Page Numbers: pp.1949-1983
  • Keywords: Flexible job shop, Heuristics, Multi objective, Metaheuristics, MULTIOBJECTIVE GENETIC ALGORITHM, SWARM OPTIMIZATION ALGORITHM, DISCRETE HARMONY SEARCH, BEE COLONY ALGORITHM, SCHEDULING PROBLEM, TABU SEARCH, EVOLUTIONARY ALGORITHMS, ROBUSTNESS MEASURES, PARETO-OPTIMALITY, DISPATCHING RULES
  • Marmara University Affiliated: Yes

Abstract

Flexible job shop scheduling problem is a relaxation of the job shop scheduling problem and is one of the well-known combinatorial optimization problems that has wide applications in the industrial fields such as production management, supply chain, transport systems, manufacturing systems. In recent years, many researches have been carried out with different approaches-ranging from mathematical models to heuristic methods-to solve multi objective flexible job shop scheduling problems (FJSSP). This study aims to present the forms of scrutiny of multi-objective FJSSPs and various heuristic techniques used to solve problems in the last decade. This review will allow the reader to select specific methods and follow the guidelines set forth in their future research.