The pickup and delivery problem: a many-objective analysis
The pickup and delivery problem (PDP) considers a set of transportation requests, which specify the quantity of product that has to be picked up from an origin and delivered to a destination. There exist a number of vehicles available to be used for completing these tasks. PDP consists of _nding a c...
| Autores: | , |
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| Tipo de recurso: | artículo |
| Estado: | Versión publicada |
| Fecha de publicación: | 2015 |
| País: | México |
| Institución: | Universidad Autónoma Metropolitana |
| Repositorio: | Concentración de Recursos de Información Científica y Académica, UAM Cuajimalpa |
| Idioma: | inglés |
| OAI Identifier: | oai:ilitia.cua.uam.mx:123456789/60 |
| Acceso en línea: | http://ilitia.cua.uam.mx:8080/jspui/handle/123456789/60 |
| Access Level: | acceso abierto |
| Palabra clave: | info:eu-repo/classification/cti/7 Optimización de Muchos Objetivos Problema de Recogida y Entrega Transporte Algoritmo Evolutivo |
| Sumario: | The pickup and delivery problem (PDP) considers a set of transportation requests, which specify the quantity of product that has to be picked up from an origin and delivered to a destination. There exist a number of vehicles available to be used for completing these tasks. PDP consists of _nding a collection of routes with mínimum cost, such that all transportation request are serviced. Traditionally, cost has been associated with the number of routes and the total travel distance. However, in many applications, some other objectives emerge, for example, the minimization of travel time and the maximization of thecollected pro_t. If we consider all these four objectives equally important, PDP can be tackled as a many-objective problem. In this paper we are interested in analyzing this many-objective problem in order to study some of its properties, speci_cally, (i) the change of di_culty when the number of objectives is increased, and (ii) the conict degree between each pair of objectives. In order to analyze these topics, we compare the performance of a recently proposed multi-objective evolutionary algorithm against that of the well-known _-MOEA, which has shown good results in many-objective problems. |
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