A particle swarm optimization for the capacitated vehicle routing problem

This paper proposed a random-key based solution representaion and decoding metdod for solving the Capacitated Vehicle Routing Problem (CVRP) using Particle Swarm Optimization (PSO). The Solution CVRP with n customers and m vehicles. The decoding method start with transforming the particle to a priority list of customer to enterroute and priority matrix of vehicle to serve each customer. The vehicle routes are constructed based on the costumer representation is applied using GLNPSO, a PSO algorithm with multiple social learning structures. The proposed algorithm is tested using the benchmark data set provided by Christofides. The computational result shows that representation ang decoding method is promising to be applied for CVRP.