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Finding Highly Preferred Points for Multi-objective Integer Programs

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dc.contributor.author Lokman, Banu
dc.contributor.author Koksalan, Murat
dc.date.accessioned 2019-06-26T07:54:47Z
dc.date.available 2019-06-26T07:54:47Z
dc.date.issued 2014
dc.identifier.issn 0740-817X
dc.identifier.issn 1545-8830
dc.identifier.uri https://doi.org/10.1080/0740817X.2014.882532
dc.identifier.uri https://acikerisim.tedu.edu.tr/xmlui/handle/20.500.12485/165
dc.description.abstract This article develops exact algorithms to generate all non-dominated points in a specified region of the criteria space in Multi-Objective Integer Programs (MOIPs). Typically, there are too many non-dominated points in large MOIPs and it is not practical to generate them all. Therefore, the problem of generating non-dominated points in the preferred region of the decision-maker is addressed. To define the preferred region, the non-dominated set is approximated using a hyper-surface. A procedure is developed that then finds a preferred hypothetical point on this surface and defines a preferred region around the hypothetical point. Once the preferred region is defined, all non-dominated points in that region are generated. The performance of the proposed approach is tested on multi-objective assignment, multi-objective knapsack, and multi-objective shortest path problems with three and four objectives. Computational results show that a small set of non-dominated points is generated that contains highly preferred points in a reasonable time. en_US
dc.language.iso en en_US
dc.publisher TAYLOR & FRANCIS INC, 530 CHESTNUT STREET, STE 850, PHILADELPHIA, PA 19106 USA en_US
dc.subject Engineering en_US
dc.subject Operations Research & Management Science en_US
dc.subject Engineering, Industrial en_US
dc.title Finding Highly Preferred Points for Multi-objective Integer Programs en_US
dc.type Article en_US
dc.relation.journal IIE Transactions
dc.identifier.issue 11
dc.identifier.startpage 1181
dc.identifier.endpage 1195
dc.identifier.volume 46


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