A bi-objective vehicle routing problem that integrates routing operations into tactical grouping decisions
Routing, Vehicles, Cluster, exact model
In this work, we consider a bi-objective vehicle routing problem in which, besides the classic minimization of the total routing cost, the operator also needs to minimize the maximum diameter of the routes, which is the maximum distance between two clients served within the same route. This problem arises in applications where, during the decision, the planner needs to integrate the routing decisions into his tactical planning in order to reduce the cost of a potential route under uncertainty. In addition to the problem description, we provide an entire linear formulation of the problem and an ad hoc method ε-constraint capable of dealing with small size problems. We also present an algorithm based on the Variable Neighborhood Search strategy for solving larger problems and a Non-Dominance Sorting Algorithm based on Genetic Algorithms. We provide an analysis of the results obtained after the execution of our algorithms in some classic instances of the problem of the capable vehicle routing. We also present some methods that will allow us to present the results using visual quality metrics.