Please use this identifier to cite or link to this item: http://hdl.handle.net/10397/55347
Title: SRBFO algorithm for production scheduling with mold and machine maintenance consideration
Authors: Niu, B
Bi, Y
Chan, FTS 
Wang, ZX
Keywords: Barterial foraging
Machine maintenance
Mold maintenance
Production scheduling
Structure redesigned
Issue Date: 2015
Publisher: Springer
Source: Lecture notes in computer science (including subseries Lecture notes in artificial intelligence and lecture notes in bioinformatics) How to cite?
Journal: Lecture notes in computer science (including subseries Lecture notes in artificial intelligence and lecture notes in bioinformatics) 
Abstract: A good production scheduling integrated with preventive maintenance scheduling scheme is significant for maintaining a higher reliability and stability for manufactory system. In this paper production scheduling problem with mold and machine maintenance (PS-MMS) consideration is studied and solved by structure-redesign-based bacterial foraging optimization (SRBFO) algorithm. PPS-MMS is a typical discrete combination optimization problem that allocating a certain number of jobs to available machine and mold and integrating maintenance activities for machine and mold with production activities. Unlike traditional maintenance activities operated with fixed duration, the maintenance duration in our PS-MMS model is varying with the usage age of machine/mold. To obtain a better solution for this difficult problem in acceptable time, SRBFO is adopted by encoding and decoding of bacteria on every dimension so that each bacterium can represent a potential solution. Five different scale instances were selected as test problems, experimental results demonstrated that SRBFO is more suitable than PSO to deal with PS-MMS problem in terms of the stability from the best solutions.
Description: 11th International Conference, ICIC 2015, Fuzhou, China, August 20-23, 2015
URI: http://hdl.handle.net/10397/55347
ISBN: 9783319221854
ISSN: 0302-9743
EISSN: 1611-3349
DOI: 10.1007/978-3-319-22186-1_73
Appears in Collections:Conference Paper

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