Um Algoritmo genético multiobjetivo para a programação integrada de veículos e tripulações
The integrated vehicle and crew scheduling problem is a hard, widely studied Combinatorial Optimization problem over the years. Taking into consideration the range of variables related to the planning process of vehicles and drivers, there are several practical characteristics of the problem that ar...
| Autor: | |
|---|---|
| Tipo de recurso: | artículo |
| Estado: | Versión publicada |
| Fecha de publicación: | 2016 |
| País: | Brasil |
| Institución: | Universidade Federal do Ceará (UFC) |
| Repositorio: | Repositório Institucional da Universidade Federal do Ceará (UFC) |
| Idioma: | portugués |
| OAI Identifier: | oai:repositorio.ufc.br:riufc/21179 |
| Acceso en línea: | http://www.repositorio.ufc.br/handle/riufc/21179 |
| Access Level: | acceso abierto |
| Palabra clave: | Transportes Otimização combinatória Pareto-based selection algorithm Transporte público |
| Sumario: | The integrated vehicle and crew scheduling problem is a hard, widely studied Combinatorial Optimization problem over the years. Taking into consideration the range of variables related to the planning process of vehicles and drivers, there are several practical characteristics of the problem that are not reflected in the solutions generated computationally. The existing models focus on minimizing costs. However, other objectives must be considered as for example the reduction of meal breaks for the crews. This paper aims at presenting a multiobjective approach for the integrated vehicle and crew scheduling problem in public transport systems based on Genetic Algorithms. Computational results with real instances are presented and discussed. These results indicate that this new approach has a considerable potential for achieving significant gains in terms of operation costs and reduction in planning times. |
|---|