Tri-Objective Vehicle Routing Problem to Optimize the Distribution Process of Sustainable Local E-Commerce Platforms

Abstract

The dramatic growth of online shopping worldwide in the last few years generated negative consequences for local small retailers who do not adopt information technologies. Furthermore, the e-commerce sector is considered a good opportunity to develop sustainable logistic processes. To reach this goal, the proposed paper presents a mathematical model and a metaheuristic algorithm to solve a multi-objective capacitated vehicle routing problem (CVRP) distinguished by economic, green, and ethical objective functions. The proposed algorithm is a multi-objective simulated annealing (MOSA) that is implemented in a software architecture and validated with real-world instances that differ for the product type delivered and the geographic distribution of customers. The main result of each test is a tri-dimensional Pareto front, i.e., a decision-support system for practitioners in selecting the best solution according to their needs. From these fronts, it can be observed that if the economic and environmental performances slightly deteriorate by 1.6% and 4.5%, respectively, the social one improves by 19.4%. Furthermore, the developed MOSA shows that the environmental and social objective functions depend on the product dimensions and the geographic distribution of customers. Regarding the former aspect, this paper reports that, counter-intuitively, the metabolic energy consumption per driver decreases with bigger products because the number of necessary vehicles (and drivers) increases, and, thus, the workload is divided among more employees. Regarding the geographic distribution, this manuscript illustrates that, despite similar traveled distances, highly variable altitudes cause more carbon emissions compared to flat distributions. Finally, this contribution shows that delivering small goods decreases the distance that vehicles travel empty by 59%, with a consequent cost reduction of 16%.