Publication:
GA with Priority Rules for Solving Job-Shop Scheduling Problems

dc.contributor.author Hasan, S. M. Kamrul en_US
dc.contributor.author Sarker, Ruhul en_US
dc.contributor.author Cornforth, David en_US
dc.date.accessioned 2021-11-25T13:33:54Z
dc.date.available 2021-11-25T13:33:54Z
dc.date.issued 2008 en_US
dc.description.abstract The Job-Shop Scheduling Problem (JSSP) is considered as one of the difficult combinatorial optimization problems and treated as a member of NP-complete problem class. In this paper, we consider JSSPs with an objective of minimizing makespan while satisfying a number of hard constraints. First, we develop a genetic algorithm (GA) based approach for solving JSSPs. We then introduce a number of priority rules such as partial reordering, gap reduction and restricted swapping to improve the performance of the GA. We run the GA incorporating these rules in a number of different ways. We solve 40 benchmark problems and compared their results with that of a number of well-known algorithms. We obtain optimal solutions for 27 problems, and the overall performance of our algorithms is quite encouraging. en_US
dc.identifier.isbn 978-1-4244-1822-0 en_US
dc.identifier.uri http://hdl.handle.net/1959.4/39964
dc.language English
dc.language.iso EN en_US
dc.publisher IEEE en_US
dc.rights CC BY-NC-ND 3.0 en_US
dc.rights.uri https://creativecommons.org/licenses/by-nc-nd/3.0/au/ en_US
dc.source Legacy MARC en_US
dc.subject.other Genetic Algorithm en_US
dc.subject.other Job-Shop Scheduling en_US
dc.subject.other Makespan en_US
dc.subject.other Heuristics en_US
dc.title GA with Priority Rules for Solving Job-Shop Scheduling Problems en_US
dc.type Conference Paper en
dcterms.accessRights open access
dspace.entity.type Publication en_US
unsw.accessRights.uri https://purl.org/coar/access_right/c_abf2
unsw.description.publisherStatement ©2008 IEEE. Personal use of this material is permitted. However, permission to reprint/republish this material for advertising or promotional purposes or for creating new collective works for resale or redistribution to servers or lists, or to reuse any copyrighted component of this work in other works must be obtained from the IEEE. en_US
unsw.identifier.doiPublisher http://dx.doi.org/10.1109/CEC.2008.4631050 en_US
unsw.publisher.place Hong Kong en_US
unsw.relation.faculty UNSW Canberra
unsw.relation.ispartofconferenceLocation Hong Kong en_US
unsw.relation.ispartofconferenceName IEEE World Congress on Evolutionary Computation en_US
unsw.relation.ispartofconferenceProceedingsTitle IEEE World Congress on Evolutionary Computation, 2008 en_US
unsw.relation.ispartofconferenceYear 2008 en_US
unsw.relation.ispartofpagefrompageto 1913-1920 en_US
unsw.relation.originalPublicationAffiliation Hasan, S. M. Kamrul, Information Technology & Electrical Engineering, Australian Defence Force Academy, UNSW en_US
unsw.relation.originalPublicationAffiliation Sarker, Ruhul, Information Technology & Electrical Engineering, Australian Defence Force Academy, UNSW en_US
unsw.relation.originalPublicationAffiliation Cornforth, David, CSIRO en_US
unsw.relation.school School of Engineering and Information Technology *
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