A Genetic Algorithm for the Multi-Depot Vehicle Routing Problem

In this paper, we focus on the optimization of the system of the spare parts distribution for authorized garages in the Czech Republic. A spare parts market belongs to one of the key elements of the car industry. However, it has to adapt to still higher requirements on accuracy, speed and minimum error rate of the deliveries with keeping the costs at its minimum at the same time. The distribution of products from depots to customers is a practical and challenging problem in logistics that opens a significant space for application of software products.The design of optimal routes of vehicles from two depots can be formulated in combinatorial optimization as a multi-depot vehicle routing problem.The goal of a multi-depot vehicle routing problem is to design routes that start and end in one of the depots and visit a subset of customers in a specific sequence. Every customer has to be visited on one of the routes and the total costs for the delivery should be minimal.Vehicle routing problems belong to the class of NP-hard problems which means that there is no efficient algorithm for finding optimal solution available. To find a solution in an efficient way, we propose an approximate method based on a genetic algorithm.