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dc.contributor.authorHazır, Ö.en_US
dc.contributor.authorGünalay, Y.en_US
dc.contributor.authorErel, E.en_US
dc.date.accessioned2016-02-08T10:09:19Z
dc.date.available2016-02-08T10:09:19Z
dc.date.issued2007en_US
dc.identifier.issn0268-3768
dc.identifier.urihttp://hdl.handle.net/11693/23128
dc.description.abstractThe customer order scheduling problem (COSP) is defined as to determine the sequence of tasks to satisfy the demand of customers who order several types of products produced on a single machine. A setup is required whenever a product type is launched. The objective of the scheduling problem is to minimize the average customer order flow time. Since the customer order scheduling problem is known to be strongly NP-hard, we solve it using four major metaheuristics and compare the performance of these heuristics, namely, simulated annealing, genetic algorithms, tabu search, and ant colony optimization. These are selected to represent various characteristics of metaheuristics: nature-inspired vs. artificially created, population-based vs. local search, etc. A set of problems is generated to compare the solution quality and computational efforts of these heuristics. Results of the experimentation show that tabu search and ant colony perform better for large problems whereas simulated annealing performs best in small-size problems. Some conclusions are also drawn on the interactions between various problem parameters and the performance of the heuristics.en_US
dc.language.isoEnglishen_US
dc.source.titleInternational Journal of Advanced Manufacturing Technologyen_US
dc.relation.isversionofhttp://dx.doi.org/10.1007/s00170-007-0998-8en_US
dc.subjectComputational complexityen_US
dc.subjectGenetic algorithmsen_US
dc.subjectHeuristic methodsen_US
dc.subjectProblem solvingen_US
dc.subjectResource allocationen_US
dc.subjectSimulated annealingen_US
dc.subjectTabu searchen_US
dc.subjectAnt colony optimizationen_US
dc.subjectCustomer order schedulingen_US
dc.subjectMetaheuristicsen_US
dc.subjectSchedulingen_US
dc.titleCustomer order scheduling problem: a comparative metaheuristics studyen_US
dc.typeArticleen_US
dc.departmentDepartment of Managementen_US
dc.citation.spage589en_US
dc.citation.epage598en_US
dc.citation.volumeNumber37en_US
dc.identifier.doi10.1007/s00170-007-0998-8en_US
dc.publisherSpringeren_US
dc.identifier.eissn1433-3015


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