A two-phase solution algorithm for the Flexible Periodic Vehicle Routing Problem
The Flexible Periodic Vehicle Routing Problem is the problem of visiting a given set of customers considering a certain periodicity to attend their demands. It is a generalization of the Periodic Vehicle Routing Problem where the fixed schedule constraint is relaxed and the quantity to deliver to ea...
| Autores: | , , |
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| Formato: | artículo |
| Fecha de publicación: | 2018 |
| País: | España |
| Recursos: | Universitat Politècnica de Catalunya (UPC) |
| Repositorio: | UPCommons. Portal del coneixement obert de la UPC |
| Idioma: | inglés |
| OAI Identifier: | oai:upcommons.upc.edu:2117/123216 |
| Acesso em linha: | https://hdl.handle.net/2117/123216 https://dx.doi.org/10.1016/j.cor.2018.05.021 |
| Access Level: | acceso abierto |
| Palavra-chave: | Combinatorial probabilities Numerical analysis--Simulation methods Flexible periodic vehicle routing Matheuristic Service frequency Probabilitats Anàlisi numèrica Classificació AMS::60 Probability theory and stochastic processes::60C05 Combinatorial probability Classificació AMS::65 Numerical analysis::65C Probabilistic methods, simulation and stochastic differential equations Àrees temàtiques de la UPC::Matemàtiques i estadística::Probabilitat Àrees temàtiques de la UPC::Matemàtiques i estadística::Investigació operativa::Programació matemàtica |
| Resumo: | The Flexible Periodic Vehicle Routing Problem is the problem of visiting a given set of customers considering a certain periodicity to attend their demands. It is a generalization of the Periodic Vehicle Routing Problem where the fixed schedule constraint is relaxed and the quantity to deliver to each customer at each visit is a decision variable. This flexibility leads to remarkable savings in total costs and this explains the interest in studying the problem and developing effective solution approaches. In this work, an iterative two-phase matheuristic is developed to solve medium and large instances of the problem. Computational tests are made on benchmark instances and on newly generated instances. The results of the matheuristic are compared to the best-known solutions, on small-size instances, and to lower bounds on larger instances. Computational results show that good quality solutions are obtained in a reasonable amount of time. |
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