Abstract
Nowadays genetic algorithms stand as a trend to solve NPcomplete and NP-hard problems. In this paper, we present a new hybrid metaheuristic which uses Parallel Genetic Algorithms and Scatter Search coupled with a decomposition-into-petals procedure for solving a class of Vehicle Routing and Scheduling Problems. The parallel genetic algorithm presented is based on the island model and was run on a cluster of workstations. Its performance is evaluated for a heterogeneous fleet problem, which is considered a problem much harder to solve than the homogeneous vehicle routing problem.
Cite
CITATION STYLE
Ochi, L. S., Vianna, D. S., Drummond, L. M. A., & Victor, A. O. (1998). A parallel evolutionary algorithm for the vehicle routing problem with heterogeneous fleet. In Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) (Vol. 1388, pp. 216–224). Springer Verlag. https://doi.org/10.1007/3-540-64359-1_691
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