Solving cell formation and task scheduling in cellular manufacturing system by discrete bacteria foraging algorithm

Chunfeng Liu, Jufeng Wang, Joseph Y.T. Leung, Kai Li

Research output: Contribution to journalArticlepeer-review

41 Scopus citations

Abstract

We consider a joint decision model of cell formation and task scheduling in cellular manufacturing system under dual-resource constrained (DRC) setting. On one hand, machines and workers are multi-functional and/or multi-skilled, and they are grouped into workstations and cells. On the other hand, there is a processing sequence among operations of the parts which needs to be dispatched to the desirable workstations for processing. Inter-cell movements of parts can reduce the processing times and the makespan but will increase the inter-cell material handling costs. The objective of the problem is to minimise the material handling costs as well as the fixed and operating costs of machines and workers. Due to the NP-hardness of the problem, we propose an efficient discrete bacteria foraging algorithm (DBFA) with elaborately designed solution representation and bacteria evolution operators to solve the proposed problem. We tested our algorithm using randomly generated instances with different sizes and settings by comparing with the original bacteria foraging algorithm and a genetic algorithm. Our results show that the proposed DBFA has better performance than the two compared algorithms with the same running time.

Original languageEnglish (US)
Pages (from-to)923-944
Number of pages22
JournalInternational Journal of Production Research
Volume54
Issue number3
DOIs
StatePublished - Feb 1 2016

All Science Journal Classification (ASJC) codes

  • Strategy and Management
  • Management Science and Operations Research
  • Industrial and Manufacturing Engineering

Keywords

  • bacteria foraging algorithm
  • cell formation
  • cellular manufacturing system
  • group scheduling
  • operation sequence

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