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Conference Paper: A novel hybrid algorithm for multi-period production scheduling of jobs in virtual cellular manufacturing systems
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TitleA novel hybrid algorithm for multi-period production scheduling of jobs in virtual cellular manufacturing systems
 
AuthorsMak, KL1
Ma, J1
 
KeywordsBacktracking
Constraint Programming
Discrete Particle Swarm Optimization
Virtual Cellular Manufacturing Systems
 
Issue Date2011
 
CitationProceedings Of The World Congress On Engineering 2011, Wce 2011, 2011, v. 1, p. 685-690 [How to Cite?]
 
AbstractVirtual cellular manufacturing has attracted a lot of attention in recent years because traditional cellular manufacturing is inadequate under a highly dynamic manufacturing environment. In this paper, a new mathematical model is established for generating optimal production schedules for virtual cellular manufacturing systems operating under a multi-period manufacturing scenario. The objective is to minimize the total manufacturing cost over the entire planning horizon. A hybrid algorithm, based on the techniques of discrete particle swarm optimization and constraint programming is proposed to solve the complex production scheduling problem. Although particle swarm optimization performs competitively with other meta-heuristics for most optimization problems, the evolution process may be stagnated as time goes on if the swarm is going to be in equilibrium, especially for problems with hard constraitns. Constraint programming, on the other hand, is an effective technique for solving problems with hard constraints. However, the technique may be inefficient if the feasible search space is very large. Therefore, the aim of the proposed hybrid algorithm is to combine the complementary advantages of particle swarm optimization and constraint programming to improve its search performance. The effectiveness of the proposed methodology is illustrated by solving a set of randomly generated test problems.
 
ReferencesReferences in Scopus
 
DC FieldValue
dc.contributor.authorMak, KL
 
dc.contributor.authorMa, J
 
dc.date.accessioned2012-08-08T09:03:35Z
 
dc.date.available2012-08-08T09:03:35Z
 
dc.date.issued2011
 
dc.description.abstractVirtual cellular manufacturing has attracted a lot of attention in recent years because traditional cellular manufacturing is inadequate under a highly dynamic manufacturing environment. In this paper, a new mathematical model is established for generating optimal production schedules for virtual cellular manufacturing systems operating under a multi-period manufacturing scenario. The objective is to minimize the total manufacturing cost over the entire planning horizon. A hybrid algorithm, based on the techniques of discrete particle swarm optimization and constraint programming is proposed to solve the complex production scheduling problem. Although particle swarm optimization performs competitively with other meta-heuristics for most optimization problems, the evolution process may be stagnated as time goes on if the swarm is going to be in equilibrium, especially for problems with hard constraitns. Constraint programming, on the other hand, is an effective technique for solving problems with hard constraints. However, the technique may be inefficient if the feasible search space is very large. Therefore, the aim of the proposed hybrid algorithm is to combine the complementary advantages of particle swarm optimization and constraint programming to improve its search performance. The effectiveness of the proposed methodology is illustrated by solving a set of randomly generated test problems.
 
dc.description.natureLink_to_subscribed_fulltext
 
dc.identifier.citationProceedings Of The World Congress On Engineering 2011, Wce 2011, 2011, v. 1, p. 685-690 [How to Cite?]
 
dc.identifier.epage690
 
dc.identifier.scopuseid_2-s2.0-80755174575
 
dc.identifier.spage685
 
dc.identifier.urihttp://hdl.handle.net/10722/158847
 
dc.identifier.volume1
 
dc.languageeng
 
dc.relation.ispartofProceedings of the World Congress on Engineering 2011, WCE 2011
 
dc.relation.referencesReferences in Scopus
 
dc.subjectBacktracking
 
dc.subjectConstraint Programming
 
dc.subjectDiscrete Particle Swarm Optimization
 
dc.subjectVirtual Cellular Manufacturing Systems
 
dc.titleA novel hybrid algorithm for multi-period production scheduling of jobs in virtual cellular manufacturing systems
 
dc.typeConference_Paper
 
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Author Affiliations
  1. The University of Hong Kong