A Sector Combination Optimization Algorithm for the Multi-Depot Vehicle Routing Problem

This paper proposes a bilevel programming method to solve the MDVRP problem, the goal is to minimize the vehicle distribution distance. On the premise of meeting the capacity of the yard and the demand of customers, the upper layer assigns customers to the depots according to the nearest distance from the depot. The lower level solves the problem of single vehicle route planning respectively, assigning customers to vehicles and planning their access sequence. In the lower level, the sector combination optimization (SCO) algorithm is used to generate multiple initial solutions. With these solutions as the initial population of genetic algorithm and ant colony algorithm, the number of iterations can be reduced to achieve fast convergence. And because of the abundant initial solutions, the algorithm can avoid trapping in local optimum. The results show that the sector combination optimization algorithm makes the initial solutions more abundant while reducing the space of the problem.