Computing Non-Stationary (S, S) Policies Using Mixed Integer Linear Programming
| dc.contributor.author | Xiang, Mengyuan | |
| dc.contributor.author | Rossi, Roberto | |
| dc.contributor.author | Martin-Barragan, Belen | |
| dc.contributor.author | Tarim, S. Armagan | |
| dc.contributor.authorID | 6641 | tr_TR |
| dc.contributor.other | 03.04. İşletme | |
| dc.contributor.other | 03. İktisadi ve İdari Birimler Fakültesi | |
| dc.contributor.other | 01. Çankaya Üniversitesi | |
| dc.date.accessioned | 2018-09-19T07:21:41Z | |
| dc.date.accessioned | 2025-09-18T12:47:48Z | |
| dc.date.available | 2018-09-19T07:21:41Z | |
| dc.date.available | 2025-09-18T12:47:48Z | |
| dc.date.issued | 2018 | |
| dc.description | Tarim, S. Armagan/0000-0001-5601-3968; Rossi, Roberto/0000-0001-7247-1010; Martin-Barragan, Belen/0000-0003-4807-2700 | en_US |
| dc.description.abstract | This paper addresses the single-item single-stocking location non-stationary stochastic lot sizing problem under the (s, S) control policy. We first present a mixed integer non-linear programming (MINLP) formulation for determining near-optimal (s, S) policy parameters. To tackle larger instances, we then combine the previously introduced MINLP model and a binary search approach. These models can be reformulated as mixed integer linear programming (MILP) models which can be easily implemented and solved by using off-the-shelf optimization software. Computational experiments demonstrate that optimality gaps of these models are less than 0.3% of the optimal policy cost and computational times are reasonable. (C) 2018 Elsevier B.V. All rights reserved. | en_US |
| dc.description.publishedMonth | 12 | |
| dc.identifier.citation | Xiang, M., Rossi, R., Martin-Barragan, B., Tarım, S.A. (2018). Computing non-stationary (s, S) policies using mixed integer linear programming. European Journal of Operational Research, 271(2), 490-500. http://dx.doi.org/10.1016/j.ejor.2018.05.030 | en_US |
| dc.identifier.doi | 10.1016/j.ejor.2018.05.030 | |
| dc.identifier.issn | 0377-2217 | |
| dc.identifier.issn | 1872-6860 | |
| dc.identifier.scopus | 2-s2.0-85048834894 | |
| dc.identifier.uri | https://doi.org/10.1016/j.ejor.2018.05.030 | |
| dc.identifier.uri | https://hdl.handle.net/123456789/11891 | |
| dc.language.iso | en | en_US |
| dc.publisher | Elsevier Science Bv | en_US |
| dc.rights | info:eu-repo/semantics/openAccess | en_US |
| dc.subject | Inventory | en_US |
| dc.subject | (S, S) Policy | en_US |
| dc.subject | Stochastic Lot-Sizing | en_US |
| dc.subject | Mixed Integer Programming | en_US |
| dc.subject | Binary Search | en_US |
| dc.title | Computing Non-Stationary (S, S) Policies Using Mixed Integer Linear Programming | en_US |
| dc.title | Computing non-stationary (s, S) policies using mixed integer linear programming | tr_TR |
| dc.type | Article | en_US |
| dspace.entity.type | Publication | |
| gdc.author.id | Tarim, S. Armagan/0000-0001-5601-3968 | |
| gdc.author.id | Rossi, Roberto/0000-0001-7247-1010 | |
| gdc.author.id | Martin-Barragan, Belen/0000-0003-4807-2700 | |
| gdc.author.institutional | Tarım, Şahap Armağan | |
| gdc.author.scopusid | 57202572816 | |
| gdc.author.scopusid | 35563636800 | |
| gdc.author.scopusid | 8369680400 | |
| gdc.author.scopusid | 6506794189 | |
| gdc.author.wosid | Tarim, S./B-4414-2010 | |
| gdc.author.wosid | Rossi, Roberto/B-4397-2010 | |
| gdc.description.department | Çankaya University | en_US |
| gdc.description.departmenttemp | [Xiang, Mengyuan; Rossi, Roberto; Martin-Barragan, Belen] Univ Edinburgh, Business Sch, Edinburgh, Midlothian, Scotland; [Tarim, S. Armagan] Cankaya Univ, Dept Management, Ankara, Turkey | en_US |
| gdc.description.endpage | 500 | en_US |
| gdc.description.issue | 2 | en_US |
| gdc.description.publicationcategory | Makale - Uluslararası Hakemli Dergi - Kurum Öğretim Elemanı | en_US |
| gdc.description.scopusquality | Q1 | |
| gdc.description.startpage | 490 | en_US |
| gdc.description.volume | 271 | en_US |
| gdc.description.woscitationindex | Science Citation Index Expanded - Social Science Citation Index | |
| gdc.description.wosquality | Q1 | |
| gdc.identifier.openalex | W2593990685 | |
| gdc.identifier.wos | WOS:000440960300009 | |
| gdc.openalex.fwci | 3.34397442 | |
| gdc.openalex.normalizedpercentile | 0.91 | |
| gdc.openalex.toppercent | TOP 10% | |
| gdc.opencitations.count | 17 | |
| gdc.plumx.mendeley | 30 | |
| gdc.plumx.scopuscites | 23 | |
| gdc.scopus.citedcount | 23 | |
| gdc.wos.citedcount | 18 | |
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