摘要
论文提出了一种改进的遗传算法求解旅行商问题(TSP)。该算法结合TSP的特点,采用实数编码方式减少算法计算复杂度;等位交叉方式扩大算法的搜索空间,改善寻优能力;轮盘赌选择策略加快算法的收敛速度。通过30个城市的benchmark实例进行仿真试验,试验结果表明,改进的遗传算法改善了全局搜索能力,具有较快的收敛速度和较高的收敛精度。
In this paper, an improved genetic algorithm for traveling salesman problem(TSP) is proposed.The algorithm combines the characteristics of TSP, using real number encoding to reduce the computational complexity of the algorithm, a cross way to expand the search space and improve searching ability, roulette selection strategy to accelerate the convergence of the algorithm.In this paper, it has simulated benchmark examples in thirty cities.The simulation results show that the improved genetic algorithm can improve the global search ability, and its convergence speed and the convergence precision is higher.
出处
《中小企业管理与科技》
2017年第9期96-98,共3页
Management & Technology of SME
关键词
旅行商问题
遗传算法
收敛速度
traveler problem
genetic algorithm
convergence precision
