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
Recommended Citation
Liu, Chunfeng; Wang, Jufeng; Leung, Joseph Y.T.; and Li, Kai, "Solving cell formation and task scheduling in cellular manufacturing system by discrete bacteria foraging algorithm" (2016). Faculty Publications. 10700.
https://digitalcommons.njit.edu/fac_pubs/10700
