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dc.contributor.authorÖzdamar, Linet
dc.date.accessioned2014-11-05T12:01:26Z
dc.date.available2014-11-05T12:01:26Z
dc.date.issued1999-02
dc.identifier.issn1094-6977
dc.identifier.urihttp://hdl.handle.net/11413/811
dc.description.abstractA genetic algorithm (GA) approach is proposed for the general resource constrained project scheduling model, in which activities may be executed in more than one operating mode and renewable as well as nonrenewable resource constraints exist, Each activity operation mode has a different duration and requires different amounts of renewable and nonrenewable resources. The objective is the minimization of the project duration or makespan, The problem under consideration is known to be one of the most difficult scheduling problems, and it is hard to find a feasible solution for such a problem, let alone the optimal one, The GA approach described here incorporates problem-specific scheduling knowledge by an indirect chromosome encoding that consists of selected activity operating modes and an ordered set of scheduling rules, The scheduling rules in the chromosome are used in an iterative scheduling algorithm that constructs the schedule resulting from the chromosome. The proposed GA is denoted as a hybrid GA (HGA) approach since it is integrated with traditional scheduling tools and expertise specifically developed for the general resource constrained project scheduling problem. The results demonstrate that HGA approach produces near-optimal solutions within a reasonable amount of computation time.tr_TR
dc.language.isoen_UStr_TR
dc.publisherIEEE-INST ELECTRICAL ELECTRONICS ENGINEERS INC, 345 E 47TH ST, NEW YORK, NY 10017-2394 USAtr_TR
dc.relationIEEE TRANSACTIONS ON SYSTEMS MAN AND CYBERNETICS PART C-APPLICATIONS AND REVIEWStr_TR
dc.subjectGenetic algorithmstr_TR
dc.subjectheuristic knowledgetr_TR
dc.subjectresource-constrainedtr_TR
dc.subjectproject schedulingtr_TR
dc.subjectgenetik algoritmalartr_TR
dc.subjectsezgisel bilgitr_TR
dc.subjectKaynak kısıtlıtr_TR
dc.subjectproje çizelgelemetr_TR
dc.titleA Genetic Algorithm Approach to a General Category Project Scheduling Problemtr_TR
dc.typeArticletr_TR
dc.identifier.wos78372300005
dc.identifier.wos78372300005en
dc.identifier.scopus2-s2.0-0002614325
dc.identifier.scopus2-s2.0-0002614325en


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