Comparison of Multiobjective Evolutionary Algorithms for Operations Scheduling under Machine Availability Constraints

Many of the problems that arise in production systems can be handled with multiobjective techniques. One of those problems is that of scheduling operations subject to constraints on the availability of machines and buffer capacity. In this paper we analyze different Evolutionary multiobjective Algor...

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Veröffentlicht in:TheScientificWorld Jg. 2013; H. 2013; S. 1 - 9
Hauptverfasser: Broz, D., Tohmé, F., Méndez, M., Frutos, M.
Format: Journal Article
Sprache:Englisch
Veröffentlicht: Cairo, Egypt Hindawi Publishing Corporation 01.01.2013
John Wiley & Sons, Inc
Wiley
Schlagworte:
Algorithms
Evolutionary algorithms
Genetic algorithms
Heuristic
Job shops
Models, Theoretical
Multiple objective analysis
Operation scheduling
Performance indices
Production scheduling
Schedules
ISSN:2356-6140, 1537-744X, 1537-744X
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Zusammenfassung:Many of the problems that arise in production systems can be handled with multiobjective techniques. One of those problems is that of scheduling operations subject to constraints on the availability of machines and buffer capacity. In this paper we analyze different Evolutionary multiobjective Algorithms (MOEAs) for this kind of problems. We consider an experimental framework in which we schedule production operations for four real world Job-Shop contexts using three algorithms, NSGAII, SPEA2, and IBEA. Using two performance indexes, Hypervolume and R2, we found that SPEA2 and IBEA are the most efficient for the tasks at hand. On the other hand IBEA seems to be a better choice of tool since it yields more solutions in the approximate Pareto frontier.
Bibliographie:ObjectType-Article-1
SourceType-Scholarly Journals-1
ObjectType-Feature-2
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Academic Editors: T. Chen and Q. Cheng
ISSN:2356-6140
1537-744X
1537-744X
DOI:10.1155/2013/418396