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Algorithms 2018, 11(3), 31; https://doi.org/10.3390/a11030031

Bilayer Local Search Enhanced Particle Swarm Optimization for the Capacitated Vehicle Routing Problem

Department of Industrial and Management Engineering, Hankuk University of Foreign Studies, Yongin 17035, Korea
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Received: 29 January 2018 / Revised: 7 March 2018 / Accepted: 13 March 2018 / Published: 15 March 2018
(This article belongs to the Special Issue Metaheuristics for Rich Vehicle Routing Problems)
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Abstract

The classical capacitated vehicle routing problem (CVRP) is a very popular combinatorial optimization problem in the field of logistics and supply chain management. Although CVRP has drawn interests of many researchers, no standard way has been established yet to obtain best known solutions for all the different problem sets. We propose an efficient algorithm Bilayer Local Search-based Particle Swarm Optimization (BLS-PSO) along with a novel decoding method to solve CVRP. Decoding method is important to relate the encoded particle position to a feasible CVRP solution. In bilayer local search, one layer of local search is for the whole population in any iteration whereas another one is applied only on the pool of the best particles generated in different generations. Such searching strategies help the BLS-PSO to perform better than the existing proposals by obtaining best known solutions for most of the existing benchmark problems within very reasonable computational time. Computational results also show that the performance achieved by the proposed algorithm outperforms other PSO-based approaches. View Full-Text
Keywords: capacitated vehicle routing problem; particle swarm optimization; novel decoding approach; bilayer local search technique capacitated vehicle routing problem; particle swarm optimization; novel decoding approach; bilayer local search technique
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Ahmed, A.K.M.F.; Sun, J.U. Bilayer Local Search Enhanced Particle Swarm Optimization for the Capacitated Vehicle Routing Problem. Algorithms 2018, 11, 31.

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