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

Document Type

Article

Publication Date

2-1-2016

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.

Identifier

84959106319 (Scopus)

Publication Title

International Journal of Production Research

External Full Text Location

https://doi.org/10.1080/00207543.2015.1113328

e-ISSN

1366588X

ISSN

00207543

First Page

923

Last Page

944

Issue

3

Volume

54

Grant

ZD03-201501

Fund Ref

National Natural Science Foundation of China

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