Scheduling With Lot Streaming In A Two-Machine Re-Entrant Flow Shop
dc.authorscopusid | 24754565700 | |
dc.authorscopusid | 36482718100 | |
dc.contributor.author | Çetinkaya, F.C. | |
dc.contributor.author | Çetinkaya, Ferda Can | |
dc.contributor.author | Duman, M. | |
dc.contributor.authorID | 50129 | tr_TR |
dc.contributor.other | Endüstri Mühendisliği | |
dc.date.accessioned | 2024-05-09T11:19:35Z | |
dc.date.available | 2024-05-09T11:19:35Z | |
dc.date.issued | 2021 | |
dc.department | Çankaya University | en_US |
dc.department-temp | Çetinkaya F.C., Department of Industrial Engineering, Çankaya University, Ankara, Turkey; Duman M., NERITA, Near East University, TRNC 10, Mersin, Turkey | en_US |
dc.description.abstract | Lot streaming is splitting a job-lot of identical items into several sublots (portions of a lot) that can be moved to the next machines upon completion so that operations on successive machines can be overlapped; hence, the overall performance of a multi-stage manufacturing environment can be improved. In this study, we consider a scheduling problem with lot streaming in a two-machine re-entrant flow shop in which each job-lot is processed first on Machine 1, then goes to Machine 2 for its second operation before it returns to the primary machine (either Machine 1 or Machine 2) for the third operation. For the two cases of the primary machine, both single-job and multi-job cases are studied independently. Optimal and near-optimal solution procedures are developed. Our objective is to minimize the makespan, which is the maximum completion time of the sublots and job lots in the single-job and multi-job cases, respectively. We prove that the single-job problem is optimally solved in polynomial-time regardless of whether the third operation is performed on Machine 1 or Machine 2. The multi-job problem is also optimally solvable in polynomial time when the third operation is performed on Machine 2. However, we prove that the multi-job problem is NP-hard when the third operation is performed on Machine 1. A global lower bound on the makespan and a simple heuristic algorithm are developed. Our computational experiment results reveal that our proposed heuristic algorithm provides optimal or near-optimal solutions in a very short time. © 2021 by the authors. Submitted for possible open access publication under the terms and conditions of the Creative Commons Attribution (CC BY) license (http://creativecommons.org/licenses/by/4.0/). | en_US |
dc.identifier.citation | Çetinkaya, Ferda Can; Duman, Mehmet. (2021). "Scheduling With Lot Streaming In A Two-Machine Re-Entrant Flow Shop", Operational Research in Engineering Sciences: Theory and Applications, Vol.4, No.3, pp.142-175. | en_US |
dc.identifier.doi | 10.31181/ORESTA111221142C | |
dc.identifier.endpage | 175 | en_US |
dc.identifier.issn | 2620-1607 | |
dc.identifier.issue | 3 | en_US |
dc.identifier.scopus | 2-s2.0-85122181673 | |
dc.identifier.scopusquality | Q1 | |
dc.identifier.startpage | 142 | en_US |
dc.identifier.uri | https://doi.org/10.31181/ORESTA111221142C | |
dc.identifier.volume | 4 | en_US |
dc.identifier.wosquality | N/A | |
dc.language.iso | en | en_US |
dc.publisher | Regional Association for Security and crisis management | en_US |
dc.relation.ispartof | Operational Research in Engineering Sciences: Theory and Applications | en_US |
dc.relation.publicationcategory | Makale - Uluslararası Hakemli Dergi - Kurum Öğretim Elemanı | en_US |
dc.rights | info:eu-repo/semantics/openAccess | en_US |
dc.scopus.citedbyCount | 3 | |
dc.subject | Lot Streaming | en_US |
dc.subject | Makespan | en_US |
dc.subject | Re-Entrant Flow Shop | en_US |
dc.subject | Scheduling | en_US |
dc.subject | Two-Machine | en_US |
dc.title | Scheduling With Lot Streaming In A Two-Machine Re-Entrant Flow Shop | tr_TR |
dc.title | Scheduling With Lot Streaming in a Two-Machine Re-Entrant Flow Shop | en_US |
dc.type | Article | en_US |
dspace.entity.type | Publication | |
relation.isAuthorOfPublication | df14a9fd-44c7-4ff0-a3c3-81ad24b82570 | |
relation.isAuthorOfPublication.latestForDiscovery | df14a9fd-44c7-4ff0-a3c3-81ad24b82570 | |
relation.isOrgUnitOfPublication | b13b59c3-89ea-4b50-b3b2-394f7f057cf8 | |
relation.isOrgUnitOfPublication.latestForDiscovery | b13b59c3-89ea-4b50-b3b2-394f7f057cf8 |