Abstract
This work presents a methodology of solution for the well-known vehicle routing problem (VRP) based on an ant colony system heuristic algorithm (ACS), which is applied to optimize the delivery process of RoSLoP (Routing-Scheduling-Loading Problem) identified in the company case of study. A first version of this algorithm models six variants of VRP and its solution satisfies the 100% of demands of the customers. The new version of the algorithm can solve 11 variants of VRP as a rich VRP. Experiments were carried out with real instances. The new algorithm shows a saving of two vehicles with regard to the first version, reducing the operation costs of the company. These results prove the viability of using heuristic methods and optimization techniques to develop new software applications.
This research was supported by CONACYT and DGEST.
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Cruz Reyes, L., Delgado Orta, J.F., González Barbosa, J.J., Torres Jimenez, J., Fraire Huacuja, H.J., Arrañaga Cruz, B.A. (2008). An Ant Colony System Algorithm to Solve Routing Problems Applied to the Delivery of Bottled Products. In: An, A., Matwin, S., Raś, Z.W., Ślęzak, D. (eds) Foundations of Intelligent Systems. ISMIS 2008. Lecture Notes in Computer Science(), vol 4994. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-540-68123-6_36
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