Hybrid simulated annealing in flow shop scheduling: A diversification and intensification approach

Nader Azizi, Ming Liang, Saeed Zolfaghari*

*Corresponding author for this work

Research output: Contribution to journalArticlepeer-review

Abstract

In the last few decades, several effective algorithms to solve combinatorial problems have been proposed. However, the challenging nature of these problems restricts the effectiveness of the conventional techniques. This paper presents a generic framework, SAMED, to tackle combinatorial optimisation problems. Based on this framework, a new algorithm tailored for Flow Shop Scheduling, SAMED-FSS, has been developed. The performance of the proposed method has been compared with other techniques including a conventional simulated annealing, a standard genetic algorithm, and a hybrid genetic algorithm. The computational results clearly indicate that the proposed algorithm is much more efficient than the conventional heuristics.

Original languageEnglish
Pages (from-to)326-348
Number of pages23
JournalInternational Journal of Industrial and Systems Engineering
Volume4
Issue number3
DOIs
Publication statusPublished - 2009

Keywords

  • evolution based diversification
  • flow shop scheduling
  • FSS
  • GA
  • genetic algorithms
  • SA
  • simulated annealing
  • Tabu search
  • TS

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