Abstract
Multi-depot Vehicle Routing Problem has great practical value to the logistics and supply chain management. The fixed distribution of vehicles variant (MDVRPFD) brings it one step closer to the practical use. Based on the simple fact that all sub-routes of an optimal route must be optimal, a new randomized best insertion (RBI) algorithm is proposed. The proposed insertion algorithm is highly effective in minimizing number of vehicles and fast. Compared to the best known result published for MDVRPFD variant, the solutions generated by this new insertion algorihtm require 20% fewer vehicles. Adopting a generalized n-op neighborhood operator, a Simulated Annealing approach yields a reduction of 12% in total distance compared to best known results of MDVRPFD.
Areas: meta-heuristic, vehicle routing, industrial applications of AI.
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© 2006 Springer-Verlag Berlin Heidelberg
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Lim, A., Zhu, W. (2006). A Fast and Effective Insertion Algorithm for Multi-depot Vehicle Routing Problem with Fixed Distribution of Vehicles and a New Simulated Annealing Approach. In: Ali, M., Dapoigny, R. (eds) Advances in Applied Artificial Intelligence. IEA/AIE 2006. Lecture Notes in Computer Science(), vol 4031. Springer, Berlin, Heidelberg. https://doi.org/10.1007/11779568_32
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DOI: https://doi.org/10.1007/11779568_32
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-540-35453-6
Online ISBN: 978-3-540-35454-3
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