Resumo:
The Vehicle Routing Problem (VRP) has wide applications in logistics and transportation
with great economic importance. VRP is a generalization of a large number of
routing problems, which consist of finding the optimal number of routes, leaving a single
depot, to serve a set of customers, minimizing routing costs and meeting a set of constraints.
The Multi Depot Vehicle Routing Problem (MDVRP) is an extension of VRP, in
which there is more than one depot distributed in a given geographic area. The rest of
the problem is identical to VRP. There are several methods for solving MDVRP such as
exact techniques, approximate algorithms and heuristics. Genetic Algorithms (GAs) are
meta-heuristics widely used to find solutions to the MDVRP problem due to the stochastic
characteristics of GAs and the efficiency in solving combinatorial problems and, for
this reason, they were selected to be applied in this work. The developed algorithm was
tested using instances present in the literature and compared with existing methodologies,
in which the genetic algorithm found good results and the work contributed to the technique
of selecting customers who can exchange between deposits. The results achieved
show that this algorithm can be evaluated in real projects, making it possible to improve
the operation of projects that face this type of problem, reducing transportation costs,
distance, delivery time, services, among other benefits.
