| Full text | |
| Author(s): |
Munari, Pedro
[1]
;
Moreno, Alfredo
[1]
;
De La Vega, Jonathan
[1]
;
Alem, Douglas
[2]
;
Gondzio, Jacek
[3, 4]
;
Morabito, Reinaldo
[1]
Total Authors: 6
|
| Affiliation: | [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
Total Affiliations: 4
|
| Document type: | Journal article |
| Source: | TRANSPORTATION SCIENCE; v. 53, n. 4, p. 1043-1066, JUL-AUG 2019. |
| Web of Science Citations: | 0 |
| Abstract | |
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) | |
| FAPESP's process: | 16/23366-9 - Models and solution methods for variants of the inventory routing problem |
| Grantee: | Pedro Augusto Munari Junior |
| Support Opportunities: | Regular Research Grants |
| FAPESP's process: | 13/07375-0 - CeMEAI - Center for Mathematical Sciences Applied to Industry |
| Grantee: | Francisco Louzada Neto |
| Support Opportunities: | Research Grants - Research, Innovation and Dissemination Centers - RIDC |
| FAPESP's process: | 15/14582-7 - Stochastic Programming and Robust Optimization to Variants of Vehicle Routing Problem: Formulations and Exact Methods |
| Grantee: | Jonathan Justen de La Vega Martínez |
| Support Opportunities: | Scholarships in Brazil - Doctorate |
| FAPESP's process: | 14/50228-0 - Formulations and solution methods for vehicle routing problems with data uncertainty |
| Grantee: | Pedro Augusto Munari Junior |
| Support Opportunities: | Regular Research Grants |
| FAPESP's process: | 15/26453-7 - Humanitarian supply chain: models and solution methods |
| Grantee: | Douglas José Alem Junior |
| Support Opportunities: | Regular Research Grants |
| FAPESP's process: | 16/01860-1 - Cutting, packing, lot-sizing, scheduling, routing and location problems and their integration in industrial and logistics settings |
| Grantee: | Reinaldo Morabito Neto |
| Support Opportunities: | Research Projects - Thematic Grants |