Abstract
The goal of the capacitated vehicle routing problem (CVRP) is to minimize the total distance of vehicle routes under the constraints of vehicles’ capacity. CVRP is classified as NP-hard problems and a number of meta-heuristic approaches have been proposed to solve the problem. This paper aims to develop a hybrid algorithm combining a discrete Particle Swarm Optimization (PSO) with Simulated Annealing (SA) to solve CVRPs. The two-stage approach of CVRP (cluster first and route second) has been adopted in the algorithm. To save computation time, a short solution representation has been adopted. The computational results demonstrate that our hybrid algorithm can effectively solve CVRPs within reasonable time.
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Kao, Y., Chen, M. (2013). Solving the CVRP Problem Using a Hybrid PSO Approach. In: Madani, K., Dourado, A., Rosa, A., Filipe, J. (eds) Computational Intelligence. IJCCI 2011. Studies in Computational Intelligence, vol 465. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-35638-4_5
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DOI: https://doi.org/10.1007/978-3-642-35638-4_5
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