| Texto completo | |
| Autor(es): |
Munari, Pedro
[1]
;
Moreno, Alfredo
[1]
;
De La Vega, Jonathan
[1]
;
Alem, Douglas
[2]
;
Gondzio, Jacek
[3, 4]
;
Morabito, Reinaldo
[1]
Número total de Autores: 6
|
| Afiliação do(s) autor(es): | [1] Univ Fed Sao Carlos, Dept Prod Engn, BR-13565905 Sao Carlos, SP - Brazil
[2] Univ Edinburgh, Business Sch, Edinburgh EH8 9JS, Midlothian - Scotland
[3] Univ Edinburgh, Sch Math, Edinburgh EH9 3FD, Midlothian - Scotland
[4] NASK Res Inst, PL-01045 Warsaw - Poland
Número total de Afiliações: 4
|
| Tipo de documento: | Artigo Científico |
| Fonte: | TRANSPORTATION SCIENCE; v. 53, n. 4, p. 1043-1066, JUL-AUG 2019. |
| Citações Web of Science: | 0 |
| Resumo | |
We address the robust vehicle routing problem with time windows (RVRPTW) under customer demand and travel time uncertainties. As presented thus far in the literature, robust counterparts of standard formulations have challenged general-purpose optimization solvers and specialized branch-and-cut methods. Hence, optimal solutions have been reported for small-scale instances only. Additionally, although the most successful methods for solving many variants of vehicle routing problems are based on the column generation technique, the RVRPTW has never been addressed by this type of method. In this paper, we introduce a novel robust counterpart model based on the well-known budgeted uncertainty set, which has advantageous features in comparison with other formulations and presents better overall performance when solved by commercial solvers. This model results from incorporating dynamic programming recursive equations into a standard deterministic formulation and does not require the classical dualization scheme typically used in robust optimization. In addition, we propose a branch-price-and-cut method based on a set partitioning formulation of the problem, which relies on a robust resource-constrained elementary shortest path problem to generate routes that are robust regarding both vehicle capacity and customer time windows. Computational experiments using Solomon's instances show that the proposed approach is effective and able to obtain robust solutions within a reasonable running time. The results of an extensive Monte Carlo simulation indicate the relevance of obtaining robust routes for a more reliable decision-making process in real-life settings. (AU) | |
| Processo FAPESP: | 16/23366-9 - Modelos e métodos de solução para variantes do problema de roteamento de estoques |
| Beneficiário: | Pedro Augusto Munari Junior |
| Modalidade de apoio: | Auxílio à Pesquisa - Regular |
| Processo FAPESP: | 13/07375-0 - CeMEAI - Centro de Ciências Matemáticas Aplicadas à Indústria |
| Beneficiário: | Francisco Louzada Neto |
| Modalidade de apoio: | Auxílio à Pesquisa - Centros de Pesquisa, Inovação e Difusão - CEPIDs |
| Processo FAPESP: | 15/14582-7 - Programação Estocástica e Otimização Robusta para Variantes do Problema de Roteamento de Veículos: Formulações e Métodos Exatos |
| Beneficiário: | Jonathan Justen de La Vega Martínez |
| Modalidade de apoio: | Bolsas no Brasil - Doutorado |
| Processo FAPESP: | 14/50228-0 - Formulations and solution methods for vehicle routing problems with data uncertainty |
| Beneficiário: | Pedro Augusto Munari Junior |
| Modalidade de apoio: | Auxílio à Pesquisa - Regular |
| Processo FAPESP: | 15/26453-7 - Cadeia de suprimentos humanitária: modelos e métodos de solução |
| Beneficiário: | Douglas José Alem Junior |
| Modalidade de apoio: | Auxílio à Pesquisa - Regular |
| Processo FAPESP: | 16/01860-1 - Problemas de corte, empacotamento, dimensionamento de lotes, programação da produção, roteamento, localização e suas integrações em contextos industriais e logísticos |
| Beneficiário: | Reinaldo Morabito Neto |
| Modalidade de apoio: | Auxílio à Pesquisa - Temático |