Vehicle routing problem using clustering algorithm by maximum neural networks

The vehicle routing problem (VRP) is one of the well known optimization problems. This paper proposes a self-organization neural network model for obtaining the best solution for VRP. Our method consists of two phases. In the first phase, the customers are grouped to several delivery areas for vehicles assignment by maximum neuron model (MNM). In the second phase, the TSP in each area is solved by the elastic net model proposed by Andrew et. al. The clustering algorithm used in the first phase is a MNM. MNM is one of the neural networks proposed by Hopfield that can minimize a cost function by considering various constraints. In the second phase, the elastic net model is used to solve the problem and it obtain good solutions of TSP. Our method improves the precision of solution, and can be extended for large-scale problems. Our simulation result shows that MNM can achieve better solutions than other methods in certain conditions.