Publication: A variable neighborhood search for minimizing total weighted tardiness with sequence dependent setup times on a single machine
dc.contributor.coauthor | N/A | |
dc.contributor.department | N/A | |
dc.contributor.department | Department of Industrial Engineering | |
dc.contributor.kuauthor | Kirlik, Gökhan | |
dc.contributor.kuauthor | Oğuz, Ceyda | |
dc.contributor.kuprofile | PhD Student | |
dc.contributor.kuprofile | Faculty Member | |
dc.contributor.other | Department of Industrial Engineering | |
dc.contributor.schoolcollegeinstitute | Graduate School of Sciences and Engineering | |
dc.contributor.schoolcollegeinstitute | College of Engineering | |
dc.contributor.yokid | N/A | |
dc.contributor.yokid | 6033 | |
dc.date.accessioned | 2024-11-09T23:12:03Z | |
dc.date.issued | 2012 | |
dc.description.abstract | This paper deals with the single machine scheduling problem to minimize the total weighted tardiness in the presence of sequence dependent setup. Firstly, a mathematical model is given to describe the problem formally. Since the problem is NP-hard, a general variable neighborhood search (GVNS) heuristic is proposed to solve it. Initial solution for the GVNS algorithm is obtained by using a constructive heuristic that is widely used in the literature for the problem. The proposed algorithm is tested on 120 benchmark instances. The results show that 37 out of 120 best known solutions in the literature are improved while 64 instances are solved equally. Next, the GVNS algorithm is applied to single machine scheduling problem with sequence dependent setup times to minimize the total tardiness problem without changing any implementation issues and the parameters of the GVNS algorithm. For this problem, 64 test instances are solved varying from small to large sizes. Among these 64 instances, 35 instances are solved to the optimality, 16 instances' best-known results are improved, and 6 instances are solved equally compared to the best-known results. Hence, it can be concluded that the GVNS algorithm is an effective, efficient and a robust algorithm for minimizing tardiness on a single machine in the presence of setup times. | |
dc.description.indexedby | WoS | |
dc.description.indexedby | Scopus | |
dc.description.issue | 7 | |
dc.description.openaccess | NO | |
dc.description.publisherscope | International | |
dc.description.volume | 39 | |
dc.identifier.doi | 10.1016/j.cor.2011.08.022 | |
dc.identifier.eissn | 1873-765X | |
dc.identifier.issn | 0305-0548 | |
dc.identifier.quartile | Q2 | |
dc.identifier.scopus | 2-s2.0-81555204394 | |
dc.identifier.uri | http://dx.doi.org/10.1016/j.cor.2011.08.022 | |
dc.identifier.uri | https://hdl.handle.net/20.500.14288/9752 | |
dc.identifier.wos | 298532900020 | |
dc.keywords | Single machine scheduling | |
dc.keywords | Weighted tardiness | |
dc.keywords | Sequence dependent setup time | |
dc.keywords | Variable neighborhood search | |
dc.keywords | Scheduling problem | |
dc.keywords | Optimization | |
dc.keywords | Algorithms | |
dc.language | English | |
dc.publisher | Pergamon-Elsevier Science Ltd | |
dc.source | Computers & Operations Research | |
dc.subject | Computer science | |
dc.subject | Engineering | |
dc.subject | Industrial engineering | |
dc.subject | Operations research | |
dc.subject | Management science | |
dc.title | A variable neighborhood search for minimizing total weighted tardiness with sequence dependent setup times on a single machine | |
dc.type | Journal Article | |
dspace.entity.type | Publication | |
local.contributor.authorid | 0000-0002-3823-908X | |
local.contributor.authorid | 0000-0003-0994-1758 | |
local.contributor.kuauthor | Kirlik, Gökhan | |
local.contributor.kuauthor | Oğuz, Ceyda | |
relation.isOrgUnitOfPublication | d6d00f52-d22d-4653-99e7-863efcd47b4a | |
relation.isOrgUnitOfPublication.latestForDiscovery | d6d00f52-d22d-4653-99e7-863efcd47b4a |