Avaliação da Meta-heurística VNS para um problema de planejamento operacional do transporte público
The Bus Driver Scheduling Problem (BDSP) consists to generate a set of drivers schedule to cover a set of vehicles schedule at the lowest cost, satisfying constraints imposed by labor laws, trade union agreements and company standards. This process is vital to the operational planning of public tran...
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| Tipo de recurso: | tesis de maestría |
| Estado: | Versión publicada |
| Fecha de publicación: | 2014 |
| País: | Brasil |
| Institución: | Universidade Estadual de Maringá (UEM) |
| Repositorio: | Repositório Institucional da Universidade Estadual de Maringá (RI-UEM) |
| Idioma: | portugués |
| OAI Identifier: | oai:localhost:1/2498 |
| Acceso en línea: | http://repositorio.uem.br:8080/jspui/handle/1/2498 |
| Access Level: | acceso abierto |
| Palabra clave: | Transporte público Escalonamento Algoritmos Algoritmos heurísticos Meta-heurística VNS Problema de escalonamento de motoristas (PEM) Brasil. Public transport Bus driver Scheduling problem Large real-world Heuristic VNS Metaheuristic Brazil. Ciências Exatas e da Terra Ciência da Computação |
| Sumario: | The Bus Driver Scheduling Problem (BDSP) consists to generate a set of drivers schedule to cover a set of vehicles schedule at the lowest cost, satisfying constraints imposed by labor laws, trade union agreements and company standards. This process is vital to the operational planning of public transportation companies since the drivers cost afIects a significant portion ofthe overall cost ofthe company. Considered NP-Hard, several works address the resolution of PEM through heuristic algorithms due to the limitations of the exact algorithms to work with large instances. The present work propose a approach for solving the BDSP involving two local search procedures in a neighborhood structure, called PCR and k-swap, in a deterministic way and in conjunction with VNS meta-heuristic. To validate the work is proposed real instances with over 2300 travei and random instances extracted of real instances. The experiments demonstrated the efficacy of VNS meta-heuristic for large instances, where the present results are compared with results reported by other studies that used PCR and k-swap procedures without the use ofVNS meta-heuristic. |
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