In this paper a real and complex transportation problem including routing, scheduling and loading tasks is presented. Most of the related works only involve the solution of routing and scheduling, as a combination of up to five different types of VRPs (Rich VRP), leaving away the loading task, which are not enough to define more complex real-world cases. We propose a solution methodology for transportation instances that involve six types of VRPs, a new constraint that limits the number of vehicles that can be attended simultaneously and the loading tasks. They are solved using an Ant Colony System algorithm, which is a distributed metaheuristic. Results from a computational test using real-world instances show that the proposed approach outperforms the transportation planning related to manual designs. Besides a well-known VRP benchmark was solved to validate the approach. © Springer-Verlag Berlin Heidelberg 2007.
CITATION STYLE
Reyes, L. C., Barbosa, J. J. G., Vargas, D. R., Huacuja, H. J. F., Valdez, N. R., Ortiz, J. A. H., … Orta, J. F. D. (2007). A distributed metaheuristic for solving a real-world scheduling-routing- loading problem. In Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) (Vol. 4742 LNCS, pp. 68–77). Springer Verlag. https://doi.org/10.1007/978-3-540-74742-0_9
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