Transiently chaotic neural network optimization algorithm for capacity vehicle routing problem

Capacity vehicle routing problem (CVRP) is an NP-hard problem. A novel approximation algorithm was presented for the problem of finding the minimum total cost of all routes in CVRP environment. The new algorithm is based on the principle of fuzzy C-means (FCM) clustering algorithm and the transiently chaotic neural network (TCNN) algorithm. FCM can group the customers with close Euclidean distance into the same vehicle according to the principle of similar feature partition, firstly. TCNN combines local search and global search, possessing high search efficiency. It will solve the routes to optimality. The computation results show that the proposed algorithm is a viable and effective approach for CVRP.