A Branch-and-Bound Algorithm for a Class of Mixed Integer Linear Maximum Multiplicative Programs: A Bi-objective Optimization Approach

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dc.contributor.authorSaghand, Payman Ghasemiko
dc.contributor.authorCharkhgard, Hadiko
dc.contributor.authorKwon, Changhyunko
dc.date.accessioned2023-08-31T02:01:18Z-
dc.date.available2023-08-31T02:01:18Z-
dc.date.created2023-08-30-
dc.date.created2023-08-30-
dc.date.issued2019-01-
dc.identifier.citationCOMPUTERS & OPERATIONS RESEARCH, v.101, pp.263 - 274-
dc.identifier.issn0305-0548-
dc.identifier.urihttp://hdl.handle.net/10203/312003-
dc.description.abstractWe present a linear programming based branch-and-bound algorithm for a class of mixed integer optimization problems with a bi-linear objective function and linear constraints. This class of optimization problems can be viewed as a special case of the problem of optimization over the set of efficient solutions in bi-objective optimization. It is known that when there exists no integer decision variable, such a problem can be solved in polynomial time. In fact, in such a case, the problem can be transformed into a Second-Order Cone Program (SOCP) and so it can be solved efficiently by a commercial solver such as CPLEX SOCP solver. However, in a recent study, it is shown that such a problem can be solved even faster in practice by using a bi-objective linear programming based algorithm. So, in this study, we embed that algorithm in an effective branch-and-bound framework to solve mixed integer instances. We also develop several enhancement techniques including preprocessing and cuts. A computational study demonstrates that the proposed branch-and-bound algorithm outperforms a commercial mixed integer SOCP solver. Moreover, the effect of different branching and node selecting strategies is explored.-
dc.languageEnglish-
dc.publisherPERGAMON-ELSEVIER SCIENCE LTD-
dc.titleA Branch-and-Bound Algorithm for a Class of Mixed Integer Linear Maximum Multiplicative Programs: A Bi-objective Optimization Approach-
dc.typeArticle-
dc.identifier.wosid000449311100019-
dc.identifier.scopusid2-s2.0-85051393300-
dc.type.rimsART-
dc.citation.volume101-
dc.citation.beginningpage263-
dc.citation.endingpage274-
dc.citation.publicationnameCOMPUTERS & OPERATIONS RESEARCH-
dc.identifier.doi10.1016/j.cor.2018.08.004-
dc.contributor.localauthorKwon, Changhyun-
dc.contributor.nonIdAuthorSaghand, Payman Ghasemi-
dc.contributor.nonIdAuthorCharkhgard, Hadi-
dc.description.isOpenAccessN-
dc.type.journalArticleArticle-
dc.subject.keywordAuthorMultiplicative programming-
dc.subject.keywordAuthorMulti-objective optimization-
dc.subject.keywordAuthorOptimization over the efficient set-
dc.subject.keywordAuthorLinear programming-
dc.subject.keywordAuthorBranch-and-bound algorithm-
dc.subject.keywordPlusEISENBERG-GALE MARKETS-
dc.subject.keywordPlusREDUNDANCY ALLOCATION-
dc.subject.keywordPlusEFFICIENT SET-
dc.subject.keywordPlusRELIABILITY-
dc.subject.keywordPlusCOMPONENTS-
dc.subject.keywordPlusGAMES-
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