基于IPSO算法的TSP问题求解研究

Study on TSP Solving Based on IPSO

为获得旅行商问题(Traveling Salesman Problem,TSP)的最优解,提出利用改进的粒子群优化(Improved Particle Swarm Optimization,IPSO)算法中求解TSP问题。IPSO算法采用了粒子自适应更新机制和继承式判断机制,克服了传统算法易陷入局部最优位置的缺陷以及可调参数和初始位置随机设定对寻优结果不确定性的影响,确保在解空间内获得一致性的全局最优解。通过对不同样本TSP问题求解,验证了IPSO算法的有效性和稳定性。对比实验表明:IPSO算法在解决大规模寻优问题时具有突出的全局寻优能力。

In order to obtain the optimal solution of TSP,an improved particle swarm optimization（IPSO）was proposed for solving TSP.By using of adaptive updating mechanism and inheritance judgment mechanism,the IPSO overcomes the shortcomings of traditional algorithm falling into local best position easily and the effect of adjustable parameters and initial position set randomly on the uncertainty of optimization results,to ensure to obtain the consistency global optimal solutions in the solution space.By solving the different samples of TSP,we verified the effectiveness and stability of the IPSO.Comparative experiment show that the IPSO in solving large-scale optimization problem has the highlighted ability about the global optimization.