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An efficient meta-heuristic algorithm for solving capacitated vehicle routing problem



This work aims to develop an enhanced Perturbation based Variable Neighborhood Search with Adaptive Selection Mechanism (PVNS ASM) to solve the capacitated vehicle routing problem (CVRP).This approach combined Perturbation based Variable Neighborhood Search (PVNS) with Adaptive Selection Mechanism (ASM) to control perturbation scheme. Instead of stochastic approach, selection of perturbation scheme used in the algorithm employed an empirical selection based on success rate of each perturbation scheme along the search. The ASM helped algorithm to get more diversification degree and jumping from local optimum condition using most successful perturbation scheme empirically in the search process. A comparative analysis with existing heuristics in the literature hasbeen performed on 21 CVRP benchmarks. The computational results proof that the developed method is competitive and very efficient in achieving high quality solution within reasonablecomputation time.


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Series Title
International Journal of Advances in Intelligent Informatics Vol 4, No 3
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Language
English
ISBN/ISSN
2442-6571
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NONE
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