Assembly line balancing using genetic algorithms

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dc.citation.epage310en_US
dc.citation.issueNumber3en_US
dc.citation.spage295en_US
dc.citation.volumeNumber11en_US
dc.contributor.authorSabuncuoğlu İ.en_US
dc.contributor.authorErel, E.en_US
dc.contributor.authorTanyer, M.en_US
dc.date.accessioned2016-02-08T10:38:07Z
dc.date.available2016-02-08T10:38:07Z
dc.date.issued2000en_US
dc.departmentDepartment of Industrial Engineeringen_US
dc.departmentDepartment of Managementen_US
dc.description.abstractAssembly Line Balancing (ALB) is one of the important problems of production/operations management area. As small improvements in the performance of the system can lead to significant monetary consequences, it is of utmost importance to develop practical solution procedures that yield high-quality design decisions with minimal computational requirements. Due to the NP-hard nature of the ALB problem, heuristics are generally used to solve real life problems. In this paper, we propose an efficient heuristic to solve the deterministic and single-model ALB problem. The proposed heuristic is a Genetic Algorithm (GA) with a special chromosome structure that is partitioned dynamically through the evolution process. Elitism is also implemented in the model by using some concepts of Simulated Annealing (SA). In this context, the proposed approach can be viewed as a unified framework which combines several new concepts of AI in the algorithmic design. Our computational experiments with the proposed algorithm indicate that it outperforms the existing heuristics on several test problems.en_US
dc.identifier.doi10.1023/A:1008923410076en_US
dc.identifier.issn0956-5515
dc.identifier.urihttp://hdl.handle.net/11693/25037
dc.language.isoEnglishen_US
dc.publisherKluwer Academic Publishersen_US
dc.relation.isversionofhttp://dx.doi.org/10.1023/A:1008923410076en_US
dc.source.titleJournal of Intelligent Manufacturingen_US
dc.subjectArtificial intelligenceen_US
dc.subjectAssembly machinesen_US
dc.subjectComputational complexityen_US
dc.subjectComputer aided manufacturingen_US
dc.subjectGenetic algorithmsen_US
dc.subjectHeuristic methodsen_US
dc.subjectJob analysisen_US
dc.subjectSimulated annealingen_US
dc.subjectAssembly line balancing (ALB)en_US
dc.subjectElitismen_US
dc.subjectProduction controlen_US
dc.titleAssembly line balancing using genetic algorithmsen_US
dc.typeArticleen_US
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