A Discrete Particle Swarm Optimization Algorithm for Solving TSP under Dynamic Topology

摘要

This paper studied the solution of the traveling salesman problem (TSP), a discrete particle swarm optimization algorithm (DPSO) model for solving this problem under dynamic topology was established. As to the discreteness and order of the TSP solution, a new coding method was designed, which included the time series connection between cities, the mapping relationship between particles and actual problems was established. And aiming at the premature convergence of the algorithm, a dynamic topology strategy based on particle mass clustering was designed to adjust the flight space of the particles. By introducing the gradient learning coefficient, the convergence speed of the algorithm and the probability of obtaining the optimal solution were improved. The simulation results showed that the proposed algorithm model can be applied to the optimization of TSP in discrete space.