Uma Huerística baseada em busca local de pareto para o Pollution-routing problem bi-objetivo

Abstract

The bi-objective Pollution-Routing Problem (b-PRP) is a PRP (Pollution-Routing Problem Bekta¸s e Laporte (2011)) extension that considers separately two conflicting objectives: minimization of carbon emission costs and minimization of operational costs. To the best of our knowledge, only few papers in the literature present multi-objective analysis concerning transportation environmental issues. Due to the lack of specific methods that are capable of finding good results for this kind of problem, this dissertation aims to propose a new heuristic method for solving the b-PRP. In this method, solution sets are generated so as to represent possible scenarios for the problem. The proposed method is based on the Two-Phase Pareto Local Search (2PPLS) proposed by Lust e Teghem (2009). During the first phase of the method, efficient solutions are generated solving parametrized problems. In the second phase, each solution is explored by means of a Pareto Local Search procedure. In other to speed up the method, an efficient scheme is employed for assessing the news solutions. Despite of its simplicity, the proposed method was capable of finding a large number of efficient solutions in a reasonable time. Computational results show that the proposed approach leads to better results than those obtained by multiobjective techniques available in the literature. The quality indicators Hypervolume (H) and R Measure (R) have been used for assessing the efficient solutions sets. Because of the random behavior presented in the sequential method used to solve the parametrized problems, Mann-Whitney Nonparametric Test has been used for comparing the results. Outperformance Relations have also been used on the results analysis. We concluded that the majority of solutions generated by 2PPLS dominates those generated by others multi-objective methods found in the literature.