Assembly line balancing using genetic algorithms

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buir.advisorSabuncuoğlu, İhsan
dc.contributor.authorTanyer, Muzaffer
dc.date.accessioned2016-01-08T20:14:42Z
dc.date.available2016-01-08T20:14:42Z
dc.date.issued1997
dc.descriptionAnkara : Department of Industrial Engineering and Institute of Engineering and Sciences, Bilkent Univ., 1997.en_US
dc.descriptionThesis (Master's) -- Bilkent University, 1997.en_US
dc.descriptionIncludes bibliographical references leaves 69-73en_US
dc.description.abstractFor the last few decades, the genetic algorithms (GAs) have been used as a kind of heuristic in many areas of manufacturing. Facility layout, scheduling, process planning, and assembly line balancing are some of the areas where GAs are already popular. GAs are more efficient than traditional heuristics and also more flexible as they allow substantial changes in the problem’s constraints and in the solution approach with small changes in the program. For this reason, GAs attract the attention of both the researchers and practitioners. Chromosome structure is one of the key components of a GA. Therefore, in this thesis, we focus on the special structure of the assembly line balancing px'oblem and design a chromosome structure that operates dynamically. We propose a new mechanism to work in parallel with GAs, namely dynamic partitioning. Different from many other GA researchers, we particularly compare different population re\asion mechanisms and the effect of elitism on these mechanisms. Elitism is revised by the simulated annealing idea and various levels of elitism are created and their effects are observed. The proposed GA is £ilso compared with the traditional heuristics.en_US
dc.description.provenanceMade available in DSpace on 2016-01-08T20:14:42Z (GMT). No. of bitstreams: 1 1.pdf: 78510 bytes, checksum: d85492f20c2362aa2bcf4aad49380397 (MD5)en
dc.description.statementofresponsibilityTanyer, Muzafferen_US
dc.format.extent73 leavesen_US
dc.identifier.urihttp://hdl.handle.net/11693/17933
dc.language.isoEnglishen_US
dc.rightsinfo:eu-repo/semantics/openAccessen_US
dc.subjectGenetic Algorithmsen_US
dc.subjectSimulated Annealingen_US
dc.subjectAssembly Line Balancingen_US
dc.subject.lccQA402.5 .T36 1997en_US
dc.subject.lcshGenetic algorithms.en_US
dc.subject.lcshAssembly-Line balancing.en_US
dc.subject.lcshLine of balance (Management)en_US
dc.titleAssembly line balancing using genetic algorithmsen_US
dc.typeThesisen_US
thesis.degree.disciplineIndustrial Engineering
thesis.degree.grantorBilkent University
thesis.degree.levelMaster's
thesis.degree.nameMS (Master of Science)

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