Solving Multi-criteria Minimum Spanning Tree Problem with Discrete Particle Swarm Optimization

The minimum spanning tree (MST) of a graph is an important concept in network design, the basic MST problem can be solved efficiently, but the multi-criteria MST (mc-MST) is NP-hard problem. In this paper, a discrete particle swarm optimization (PSO) approach is developed to deal with this problem. The principles of mutation and crossover operator in the genetic algorithm (GA) are incorporated into the proposed PSO algorithm to achieve a better diversity and break away from local optima. In the end, an enumeration method of Chen's is used to evaluate the algorithm's performance and the results show that this algorithm is efficient and feasible.