Busca avançada
Ano de início
Entree
(Referência obtida automaticamente do Web of Science, por meio da informação sobre o financiamento pela FAPESP e o número do processo correspondente, incluída na publicação pelos autores.)

A branch-and-bound algorithm for the maximum capture problem with random utilities

Texto completo
Autor(es):
Freire, Alexandre S. [1] ; Moreno, Eduardo [2] ; Yushimito, Wilfredo F. [2]
Número total de Autores: 3
Afiliação do(s) autor(es):
[1] Univ Sao Paulo, Escola Artes Ciencias & Humanidades, Sao Paulo - Brazil
[2] Univ Adolfo Ibanez, Fac Sci & Engn, Santiago - Chile
Número total de Afiliações: 2
Tipo de documento: Artigo Científico
Fonte: European Journal of Operational Research; v. 252, n. 1, p. 204-212, JUL 1 2016.
Citações Web of Science: 1
Resumo

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. (AU)

Processo FAPESP: 13/03447-6 - Estruturas combinatórias, otimização e algoritmos em Teoria da Computação
Beneficiário:Carlos Eduardo Ferreira
Linha de fomento: Auxílio à Pesquisa - Temático
Processo FAPESP: 12/17585-9 - Técnicas de modelagem para resolução de problemas de otimização combinatória
Beneficiário:Alexandre da Silva Freire
Linha de fomento: Bolsas no Brasil - Pós-Doutorado