The capacitated vehicle routing problem with soft time windows and stochastic travel times
A full multiobjective approach is employed in this paper to deal with a stochastic multiobjective capacitated vehicle routing problem (CVRP). In this version of the problem, the demand is considered to be deterministic, but the travel times are assumed to be stochastic. A soft time window is tied to...
- Autores:
- Tipo de recurso:
- Fecha de publicación:
- 2019
- Institución:
- Universidad Pedagógica y Tecnológica de Colombia
- Repositorio:
- RiUPTC: Repositorio Institucional UPTC
- Idioma:
- eng
- OAI Identifier:
- oai:repositorio.uptc.edu.co:001/14229
- Acceso en línea:
- https://revistas.uptc.edu.co/index.php/ingenieria/article/view/8782
https://repositorio.uptc.edu.co/handle/001/14229
- Palabra clave:
- genetic algorithms
heuristic algorithms
multiobjective programming
random processes
vehicle routing
algoritmos genéticos
algoritmos heurísticos
optimización multiobjetivo
proceso aleatorio
ruteo de vehículos
- Rights
- License
- http://purl.org/coar/access_right/c_abf7
Summary: | A full multiobjective approach is employed in this paper to deal with a stochastic multiobjective capacitated vehicle routing problem (CVRP). In this version of the problem, the demand is considered to be deterministic, but the travel times are assumed to be stochastic. A soft time window is tied to every customer and there is a penalty for starting the service outside the time window. Two objectives are minimized, the total length and the time window penalty. The suggested solution method includes a non-dominated sorting genetic algorithm (NSGA) together with a variable neighborhood search (VNS) heuristic. It was tested on instances from the literature and compared to a previous solution approach. The suggested method is able to find solutions that dominate some of the previously best known stochastic multiobjective CVRP solutions. |
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