Open Access

ARTICLE

A complexity task of optimization in logistic distribution: A new approach to the green multi-objective vehicle routing problem

Júlio César Ferreira¹, Maria Teresinha Arns Steiner¹

1 Pontificia Universidade Católica do Paraná PUCPR

* Corresponding Authors: Júlio César Ferreira (), Maria Teresinha Arns Steiner ()

Revista Internacional de Métodos Numéricos para Cálculo y Diseño en Ingeniería 2022, 38(1), 1-17. https://doi.org/10.23967/j.rimni.2022.01.001

Accepted 10 January 2022; Issue published 14 January 2022

Abstract

Logistic distribution involves many costs for organizations. Therefore, opportunities for optimization in this respect are always welcome. The purpose of this work is to present a methodology to provide a solution to a complexity task of optimization in Multi-objective Optimization for Green Vehicle Routing Problem (MOOGVRP). The methodology, illustrated using a case study (employee transport problem) and instances from the literature, was divided into three stages: Stage 1, “data treatment”, where the asymmetry of the routes to be formed and other particular features were addressed; Stage 2, “metaheuristic approaches” (hybrid or non-hybrid), used comparatively, more specifically: NSGA-II (Non-dominated Sorting Genetic Algorithm II), MOPSO (Multi-Objective Particle Swarm Optimization), which were compared with the new approaches proposed by the authors, CWNSGA-II (Clarke and Wright’s Savings with the Non-dominated Sorting Genetic Algorithm II) and CWTSNSGA-II (Clarke and Wright’s Savings, Tabu Search and Non-dominated Sorting Genetic Algorithm II); and, finally, Stage 3, “analysis of the results”, with a comparison of the algorithms. Using the same parameters as the current solution, an optimization of 5.2% was achieved for Objective Function 1 (OF₁ ; minimization of CO₂ emissions) and 11.4% with regard to Objective Function 2 (OF₂ ; minimization of the difference in demand), with the proposed CWNSGA-II algorithm showing superiority over the others for the approached problem. Furthermore, a complementary scenario was tested, meeting the constraints required by the company concerning time limitation. For the instances from the literature, the CWNSGA-II and CWTSNSGA-II algorithms achieved superior results.

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Keywords

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