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Large Neighborhood Search for Periodic Electric Vehicle Routing Problem

Tayeb Kouider 1 Wahiba Ramdane Cherif-Khettaf 1 Ammar Oulamara 1 
1 OPTIMIST - OPTImisation Methods for Integrated SysTems
LORIA - NSS - Department of Networks, Systems and Services
Abstract : In this paper, we address the Periodic Electric Vehicle Routing Problem, named PEVRP. This problem is motivated by a real-life industrial application and it is defined by a planning horizon of several periods typically ”days”, in which each customer has a set of allowed visit days and must be served once in the time horizon. The whole demand of each customer must be fulfilled all together. A limited fleet of electric vehicles is available at the depot. The EVs could be charged during their trips at the depot and in the available external charging stations. The objective of the PEVRP is to minimize the total cost of routing and charging over the time horizon. We propose a Large Neighborhood Search (LNS) framework for solving the PEVRP. Different implementation schemes of the proposed method including customer and station insertion strategies, three destroy operators and three insertion operators are tested on generalized benchmark instances. The computational results show that LNS prod uces competitive results compared to results obtained in previous studies. An analysis of the performance of the proposed operators is also presented.
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Submitted on : Thursday, October 29, 2020 - 1:47:10 AM
Last modification on : Wednesday, November 3, 2021 - 7:57:22 AM

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Tayeb Kouider, Wahiba Ramdane Cherif-Khettaf, Ammar Oulamara. Large Neighborhood Search for Periodic Electric Vehicle Routing Problem. 8th International Conference on Operations Research and Enterprise Systems, Feb 2019, Prague, Czech Republic. pp.169-178, ⟨10.5220/0007409201690178⟩. ⟨hal-02982812⟩



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