SRBFO algorithm for production scheduling with mold and machine maintenance consideration

Ben Niu; Ying Bi; Tung Sun Chan; Z. X. Wang

doi:10.1007/978-3-319-22186-1_73

SRBFO algorithm for production scheduling with mold and machine maintenance consideration

Ben Niu, Ying Bi, Tung Sun Chan, Z. X. Wang

Research output: Chapter in book / Conference proceeding › Conference article published in proceeding or book › Academic research › peer-review

2 Citations (Scopus)

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.

Original language	English
Title of host publication	Intelligent Computing Theories and Methodologies - 11th International Conference, ICIC 2015, Proceedings
Publisher	Springer Verlag
Pages	733-741
Number of pages	9
ISBN (Print)	9783319221854
DOIs	https://doi.org/10.1007/978-3-319-22186-1_73
Publication status	Published - 1 Jan 2015
Event	11th International Conference on Intelligent Computing, ICIC 2015 - Fuzhou, China Duration: 20 Aug 2015 → 23 Aug 2015

Publication series

Name	Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Volume	9226
ISSN (Print)	0302-9743
ISSN (Electronic)	1611-3349

Conference

Conference	11th International Conference on Intelligent Computing, ICIC 2015
Country/Territory	China
City	Fuzhou
Period	20/08/15 → 23/08/15

Keywords

Barterial foraging
Machine maintenance
Mold maintenance
Production scheduling
Structure redesigned

ASJC Scopus subject areas

Theoretical Computer Science
General Computer Science

More information

10.1007/978-3-319-22186-1_73

Cite this

Niu, B., Bi, Y., Chan, T. S., & Wang, Z. X. (2015). SRBFO algorithm for production scheduling with mold and machine maintenance consideration. In Intelligent Computing Theories and Methodologies - 11th International Conference, ICIC 2015, Proceedings (pp. 733-741). (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); Vol. 9226). Springer Verlag. https://doi.org/10.1007/978-3-319-22186-1_73

Niu, Ben ; Bi, Ying ; Chan, Tung Sun et al. / SRBFO algorithm for production scheduling with mold and machine maintenance consideration. Intelligent Computing Theories and Methodologies - 11th International Conference, ICIC 2015, Proceedings. Springer Verlag, 2015. pp. 733-741 (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)).

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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.",

keywords = "Barterial foraging, Machine maintenance, Mold maintenance, Production scheduling, Structure redesigned",

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Niu, B, Bi, Y, Chan, TS & Wang, ZX 2015, SRBFO algorithm for production scheduling with mold and machine maintenance consideration. in Intelligent Computing Theories and Methodologies - 11th International Conference, ICIC 2015, Proceedings. Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), vol. 9226, Springer Verlag, pp. 733-741, 11th International Conference on Intelligent Computing, ICIC 2015, Fuzhou, China, 20/08/15. https://doi.org/10.1007/978-3-319-22186-1_73

SRBFO algorithm for production scheduling with mold and machine maintenance consideration. / Niu, Ben; Bi, Ying; Chan, Tung Sun et al.
Intelligent Computing Theories and Methodologies - 11th International Conference, ICIC 2015, Proceedings. Springer Verlag, 2015. p. 733-741 (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); Vol. 9226).

Research output: Chapter in book / Conference proceeding › Conference article published in proceeding or book › Academic research › peer-review

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AU - Bi, Ying

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N2 - 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.

AB - 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.

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Niu B, Bi Y, Chan TS, Wang ZX. SRBFO algorithm for production scheduling with mold and machine maintenance consideration. In Intelligent Computing Theories and Methodologies - 11th International Conference, ICIC 2015, Proceedings. Springer Verlag. 2015. p. 733-741. (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)). doi: 10.1007/978-3-319-22186-1_73

SRBFO algorithm for production scheduling with mold and machine maintenance consideration

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Keywords

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