"Bi-Objective CVRP solved using a novel metaheuristic ILS Based on Decomposition"
Luis Galindres, Ramón Gallego and Frederico Guimaraes

Vehicle routing (VRP) has usually been studied with a single objective function, which is defined by the distances associated with the routing of vehicles. The goal is to design a route or set of routes to meet the demands of customers at minimum cost. However, in real life, it is necessary to consider other objective functions as well, such as social aspects related functions, which take into account equity considerations such as drivers’ workload balance. This has allowed a growth in both the formulation of multi-objective models and in the exact and approximate solution techniques. 

In particular, in this paper, the bi-objective Capacitated Vehicle Routing Problem (bi-objective CVRP) is addressed taking into account economic and social objectives. The economic objective is to minimize the cost associated with the CVRP route design, the social objective is to balance the workload of each of the drivers. 

In this work we introduce an ILS metaheuristic based on decomposition to find approximations of Pareto fronts. Different metrics will be used that determine both the quality of the solutions and the validation of the proposed metaheuristic.