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Author Ljubic, I.; Moreno, E.
Title Outer approximation and submodular cuts for maximum capture facility location problems with random utilities Type
Year 2018 Publication European Journal Of Operational Research Abbreviated Journal Eur. J. Oper. Res.
Volume 266 Issue 1 Pages 46-56
Keywords Combinatorial optimization; Branch-and-cut; Maximum capture; Random utility model; Competitive facility location
Abstract We consider a family of competitive facility location problems in which a “newcomer” company enters the market and has to decide where to locate a set of new facilities so as to maximize its market share. The multinomial logit model is used to estimate the captured customer demand. We propose a first branch-and-cut approach for this family of difficult mixed-integer non-linear problems. Our approach combines two types of cutting planes that exploit particular properties of the objective function: the first one are the outer-approximation cuts and the second one are the submodular cuts. The approach is computationally evaluated on three datasets from the recent literature. The obtained results show that our new branch-and-cut drastically outperforms state-of-the-art exact approaches, both in terms of the computing times, and in terms of the number of instances solved to optimality. (C) 2017 Elsevier B.V. All rights reserved.
Address [Ljubic, Ivana] ESSEC Business Sch, 3 Av Bernard Hirsch,BP 50105, F-95021 Cergy Pontoise, France, Email: ivana.ljubic@essec.edu;
Corporate Author Thesis
Publisher Elsevier Science Bv Place of Publication Editor
Language English Summary Language Original Title
Series Editor Series Title Abbreviated Series Title
Series Volume Series Issue Edition
ISSN 0377-2217 ISBN Medium
Area Expedition Conference
Notes WOS:000423646500005 Approved
Call Number UAI @ eduardo.moreno @ Serial 815
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Author Freire, A.S.; Moreno, E.; Yushimito, W.F.
Title A branch-and-bound algorithm for the maximum capture problem with random utilities Type
Year 2016 Publication European Journal Of Operational Research Abbreviated Journal Eur. J. Oper. Res.
Volume 252 Issue 1 Pages 204-212
Keywords Facility location; Branch and bound; Maximum capture; Random utility model
Abstract The MAXIMUM CAPTURE PROBLEM WITH RANDOM UTILITIES seeks to locate new facilities in a competitive market such that the captured demand of users is maximized, assuming that each individual chooses among all available facilities according to the well-know a random utility model namely the multinomial logit. The problem is complex mostly due to its integer nonlinear objective function. Currently, the most efficient approaches deal with this complexity by either using a nonlinear programing solver or reformulating the problem into a Mixed-Integer Linear Programing (MILP) model. In this paper, we show how the best MILP reformulation available in the literature can be strengthened by using tighter coefficients in some inequalities. We also introduce a new branch-and-bound algorithm based on a greedy approach for solving a relaxation of the original problem. Extensive computational experiments are presented, bench marking the proposed approach with other linear and non-linear relaxations of the problem. The computational experiments show that our proposed algorithm is competitive with all other methods as there is no method which outperforms the others in all instances. We also show a large-scale real instance of the problem, which comes from an application in park-and-ride facility location, where our proposed branch-and-bound algorithm was the most effective method for solving this type of problem. (C) 2015 Elsevier B.V. All rights reserved.
Address [Moreno, Eduardo; Yushimito, Wilfredo F.] Univ Adolfo Ibanez, Fac Sci & Engn, Santiago, Chile, Email: afreire@ime.usp.br;
Corporate Author Thesis
Publisher Elsevier Science Bv Place of Publication Editor
Language English Summary Language Original Title
Series Editor Series Title Abbreviated Series Title
Series Volume Series Issue Edition
ISSN 0377-2217 ISBN Medium
Area Expedition Conference
Notes WOS:000371939700018 Approved
Call Number UAI @ eduardo.moreno @ Serial 601
Permanent link to this record