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) applied to a transport passenger’s problem. For that, it was considered two objective functions (environmental issues and also balancing work between the routes) ensuring savings and satisfaction for the users. The methodology, 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.
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 [...]
This article aims to present research conducted on the literature regarding Multi-objective Optimization (MOO) for routing problems with environmental considerations (EC), referred to here as Multi-objective Optimization for the Green Vehicle Routing Problem (MOOGVRP). A Brazilian database, CAPES (Coordination for the Improvement of Higher Education Personnel), was used to collect articles of general application, case studies and reviews in English starting from, since 2012. The terms “green vehicle routing problem” (GVRP), “pollution routing problem” (PRP), “vehicle routing problem in reverse logistics” (VRPRL) and “multi-objective” were used in the research protocol. Consequently, this study obtained 1,744 research results that, following the application of the filtering criterion, resulted in a sample of 76 articles from 38 journals, for which a bibliometric data (bibliometric review) survey was conducted. When dealing with the bibliometric data of the sample, it was possible to identify information such as the number of publications per year and types of published works. Information was also identified regarding the most frequently used journals and the countries and institutions that published the most articles on the proposed theme. It was also possible to analyze the frequency of the protocol terms in the title, abstracts and keywords, the relationship between taxonomies, vehicle fleet types, multi-objective procedures, and VRP procedures. Information was also found regarding solution procedures, number of objectives, and programming languages for computational implementation, the frequency of the most used objectives, and the most cited articles in the sample. The originality of this article lies in how the research is presented, highlighting the results and particular details obtained through the survey, which may be considered of great academic importance in the sense of guiding the trends for future research.
Abstract This article aims to present research conducted on the literature regarding Multi-objective Optimization (MOO) for routing problems with environmental considerations (EC), [...]
A complexity task of optimization in logistic distribution: A new approach to the green multi-objective vehicle routing problem 
