Fuzzy heuristic approaches to the warm/cold lot sizing problem

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dc.authorscopusid25122060200
dc.authorscopusid24605261900
dc.authorscopusid14521673500
dc.contributor.authorAltay, A.
dc.contributor.authorEkinci, Y.
dc.contributor.authorToy, A.O.
dc.date.accessioned2024-07-18T20:17:59Z
dc.date.available2024-07-18T20:17:59Z
dc.date.issued2014
dc.descriptionComputer and Industrial Engineering;et al.;Gaziantep University;Istanbul Commercial University;Journal of Intelligent Manufacturing Systems;Sakarya University, Department of Industrial Engineeringen_US
dc.descriptionJoint International Symposium on "The Social Impacts of Developments in Information, Manufacturing and Service Systems" 44th International Conference on Computers and Industrial Engineering, CIE 2014 and 9th International Symposium on Intelligent Manufacturing and Service Systems, IMSS 2014 -- 14 October 2014 through 16 October 2014 -- -- 110500en_US
dc.description.abstractWe consider the dynamic lot-sizing problem with warm/cold process, which has been introduced by Toy and Berk [3]. The system parameters are: horizon length, demand at each period, production capacity at each period, warm system threshold, setup cost, inventory carrying cost and warming cost. The objective is to find the cost minimizing production scheme throughout the horizon. Under the warm/cold system setting if the production quantity in a given period is at least as much as a pre-specified level (threshold), the process can be kept warm on the next period by incurring warming cost. If, however, the production quantity is below the threshold, the process will have to start next period cold. When the process is warm, the production can start without incurring any setup cost, whereas the production of a cold process requires a cold setup cost. We extend the current literature by incorporating the fuzzy parameters where (i) the demand, and (ii) warm system threshold are fuzzy numbers. We introduce "fuzzy silver meal algorithm", "fuzzy part period algorithm", and "fuzzy least unit cost algorithm" in the existence of warm/cold process setting. Our numerical study consists of comparison of suggested algorithms based of various performance criteria.en_US
dc.identifier.endpage333en_US
dc.identifier.scopus2-s2.0-84923858688en_US
dc.identifier.scopusqualityN/Aen_US
dc.identifier.startpage320en_US
dc.identifier.urihttps://hdl.handle.net/11411/6815
dc.indekslendigikaynakScopusen_US
dc.language.isoenen_US
dc.publisherComputers and Industrial Engineeringen_US
dc.relation.ispartofCIE 2014 - 44th International Conference on Computers and Industrial Engineering and IMSS 2014 - 9th International Symposium on Intelligent Manufacturing and Service Systems, Joint International Symposium on "The Social Impacts of Developments in Information, Manufacturing and Service Systems" - Proceedingsen_US
dc.relation.publicationcategoryKonferans Öğesi - Uluslararası - Kurum Öğretim Elemanıen_US
dc.rightsinfo:eu-repo/semantics/closedAccessen_US
dc.subjectFuzzy Systemsen_US
dc.subjectHeuristicsen_US
dc.subjectLot Sizingen_US
dc.subjectWarm/Cold Processen_US
dc.subjectAlgorithmsen_US
dc.subjectFuzzy Setsen_US
dc.subjectFuzzy Systemsen_US
dc.subjectHeuristic Methodsen_US
dc.subjectManufactureen_US
dc.subjectHeuristic Approachen_US
dc.subjectHeuristicsen_US
dc.subjectLot Sizingen_US
dc.subjectLot Sizing Problemsen_US
dc.subjectPerformance Criterionen_US
dc.subjectProduction Capacityen_US
dc.subjectProduction Quantityen_US
dc.subjectProduction Schemesen_US
dc.subjectCostsen_US
dc.titleFuzzy heuristic approaches to the warm/cold lot sizing problem
dc.typeConference Object

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