Combining Genetic Algorithm with Constructive and Refinement Heuristics for Solving the Capacitated Vehicle Routing Problem

Abstract : This work presents a hybrid strategy for optimization of Capacitated Vehicle Routing Problem (CVRP) that employs Genetic Algorithms (GA) combined with the heuristics of Gillett & Miller (GM) and Hill Climbing (HC). The first heuristic is used to incorporate feasible solutions in the initial population of the GA while the second is responsible for the refinement of solutions after a certain number of generations without improvements. The computational experiments showed that the proposed strategy presented good results for the optimization of CVRP with respect to the quality of solutions well as the computational cost.
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Communication dans un congrès
IFIP International Conference on Advances in Production Management Systems (APMS), Sep 2016, Iguassu Falls, Brazil. IFIP Advances in Information and Communication Technology, AICT-488, pp.113-121, 2016, Advances in Production Management Systems. Initiatives for a Sustainable World. 〈10.1007/978-3-319-51133-7_14〉
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Stanley Lima, Renato Santos, Sidnei Araujo, Pedro Schimit. Combining Genetic Algorithm with Constructive and Refinement Heuristics for Solving the Capacitated Vehicle Routing Problem. IFIP International Conference on Advances in Production Management Systems (APMS), Sep 2016, Iguassu Falls, Brazil. IFIP Advances in Information and Communication Technology, AICT-488, pp.113-121, 2016, Advances in Production Management Systems. Initiatives for a Sustainable World. 〈10.1007/978-3-319-51133-7_14〉. 〈hal-01615793〉

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