Title: Solving a stochastic programming with recourse model for the stochastic electric capacitated vehicle routing problem using a hybrid genetic algorithm

Authors: Elhassania Messaoud

Addresses: Hassania School of Public Works, Casablanca, Morocco

Abstract: This study considers stochastic travel times in an electric capacited vehicle routing problem (ECVRP), where the used electric vehicles may need to visit charging stations due to their battery capacities. The main goal of the present paper is to solve a two-stage stochastic programming with recourse (SPR) model for this problem using a hybrid genetic algorithm (HGA) and a Monte Carlo sampling (MCS) procedure. To show the effectiveness of the proposed approach, the computational experiments are applied to 29 instances with up to 100 customers derived from benchmarks presented in the literature. Firstly the numerical results are compared to those found by CPLEX solver for the deterministic model, thereafter a very large number of scenarios is taken into consideration to evaluate this approach in the stochastic environment using a known probability distribution. [Received: 26 September 2020; Accepted: 5 February 2021]

Keywords: transport problem; electric vehicles; capacity constraint; stochastic travel times; stochastic programming with recourse model; genetic algorithm.

DOI: 10.1504/EJIE.2022.119367

European Journal of Industrial Engineering, 2022 Vol.16 No.1, pp.71 - 90

Received: 26 Sep 2020
Accepted: 05 Feb 2021

Published online: 01 Dec 2021 *

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