Intuitionistic Fuzzy Hybrid Discrete Particle Swarm Optimization for Solving Travelling Salesman Problem

Abstract

Abstract. An intuitionistic fuzzy hybrid discrete particle swarm optimization (IF-HDPSO) is proposed for solving travelling salesman problem (TSP). By defining intuitionistic fuzzy charisma function, the IF-HDPSO algorithm exploits some other individuals to participate in the updates of velocity and position except the best one. In addition, the PSO identical factor function is defined to adjust inertia weight and learning operator adaptively, so the IF-HDPSO can explore the whole optimal solution quickly. Furthermore, an adaptive genetic algorithm based on elitist reserving strategy is developed, and combine it with PSO to reduce the probability of being trapped in the local optima and premature convergence. The simulation results indicate IF-HDPSO perform better on precision, iteration number and computational robustness.