Hybrid monkey search algorithm for flow shop scheduling problem under makespan and total flow time

MARICHELVAM M., TOSUN Ö., GEETHA M.

Applied Soft Computing Journal, vol.55, pp.82-92, 2017 (SCI-Expanded) identifier identifier

  • Publication Type: Article / Article
  • Volume: 55
  • Publication Date: 2017
  • Doi Number: 10.1016/j.asoc.2017.02.003
  • Journal Name: Applied Soft Computing Journal
  • Journal Indexes: Science Citation Index Expanded (SCI-EXPANDED), Scopus
  • Page Numbers: pp.82-92
  • Keywords: Flow shop, Scheduling, NP-hard, Monkey search algorithm, Makespan, Total flow time, ITERATED GREEDY ALGORITHM, GENETIC ALGORITHM, SEQUENCING PROBLEM, PERMUTATION, MINIMIZATION, HEURISTICS, FLOWSHOPS, CRITERION
  • Akdeniz University Affiliated: Yes

Abstract

© 2017 Elsevier B.V.This paper addresses a sub-population based hybrid monkey search algorithm to solve the flow shop scheduling problem which has been proved to be non-deterministic polynomial time hard (NP-hard) type combinatorial optimization problems. Minimization of makespan and total flow time are the objective functions considered. In the proposed algorithm, two different sub-populations for the two objectives are generated and different dispatching rules are used to improve the solution quality. To the best of our knowledge, this is the first application of monkey search algorithm to solve the flow shop scheduling problems. The performance of the proposed algorithm has been tested with the benchmark problems addressed in the literature. Computational results reveal that the proposed algorithm outperforms many other heuristics and meta-heuristics addressed in the literature.