摘要
TSP问题是典型的NP难组合优化问题,而遗传算法是求解此类问题的一种方法。但遗传算法存在收敛速度慢和陷入局部最优的问题。针对上述问题并结合TSP的特点提出了一种改进的遗传算法,对传统遗传算法的各种操作与算子进行了优化与改进,较好地解决了种群多样性与算法收敛性的矛盾。实验结果表明,改进后的算法明显优于传统遗传算法,说明该算法具有良好的有效性与可行性。
TSP is a classical NP-hard combinational optimization problem.GA is a method for solving this problem.But GA has problems of slow convergence and local optimum.To solve the problems,this paper puts forward an improved genetic algorithm considering the characteristic of TSP.Every operation in traditional genetic algorithm is optimized in the improved algorithm.The new algorithm can solve the conflict between population diversity and algorithm convergence.The experimental results show that the improved algorithm is superior to the traditional genetic algorithm and has good validity and feasibility.
出处
《软件导刊》
2011年第2期52-54,共3页
Software Guide
