A multi-objective ant colony system algorithm for flow shop scheduling problem

YAĞMAHAN B., YENİSEY M. M.

EXPERT SYSTEMS WITH APPLICATIONS, vol.37, no.2, pp.1361-1368, 2010 (SCI-Expanded) identifier identifier

  • Publication Type: Article / Article
  • Volume: 37 Issue: 2
  • Publication Date: 2010
  • Doi Number: 10.1016/j.eswa.2009.06.105
  • Journal Name: EXPERT SYSTEMS WITH APPLICATIONS
  • Journal Indexes: Science Citation Index Expanded (SCI-EXPANDED), Scopus
  • Page Numbers: pp.1361-1368
  • Keywords: Flow shop scheduling, Multi-objective, Makespan, Flowtime, Heuristics, Ant colony optimization, TABU SEARCH ALGORITHM, OPTIMIZATION ALGORITHM, GENETIC ALGORITHMS, M-MACHINE, MINIMIZE, MAKESPAN, TIME
  • Bursa Uludag University Affiliated: Yes

Abstract

In this paper, we consider the flow shop scheduling problem with respect to the both objectives of makespan and total flowtime. This problem is known to be NP-hard type in literature Several algorithms have been proposed to solve this problem We present a multi-objective ant colony system algorithm (MOACSA). which combines ant colony optimization approach and a local search strategy in order to solve this scheduling problem. The proposed algorithm is tested with well-known problems in literature Its solution performance was compared with the existing multi-objective heuristics. The Computational results show that proposed algorithm is more efficient and better than other methods compared (C) 2009 Elsevier Ltd. All rights reserved