Discrete particle swarm optimization algorithm for weighted traveling salesman problem

In traveling salesman problem, transportation cost is determined by not only distance, but also the cargo weight on the way. Influence of cargo weight on transportation cost is analyzed, and a weighted traveling salesman problem (WTSP) model is given. In WTSP model, cities with larger demands should have priority to be served for minimal cost. A discrete particle swarm optimization algorithm named DPSO is proposed, in which the inertia weight is adjusted by a linear decreasing function of time. Comparison analysis between DPSO and existing algorithms has been done, and simulation results show that the new algorithm is reasonable and effective.