一种基于近邻策略求TSP问题的改进演化算法

摘要

For the shortcomings of greed evolutionary algorithm ( CEA) in solving the traveling salesman problem, such as small-scale, low success rate, this paper induces Inver-over down different operators, and greedy operators, improves close neighbor optimization, mapping operator, mutation operator strategy, proposes a new and improved evolutionary algorithm to solve the me-dium-scale traveling salesman problem (TSP). Simulation results verify that the evolutionary algorithm converges fast, and is of the advantages of a high success rate, better stability.%针对贪心演化算法(GEA)在旅行商问题中存在的求解规模小、成功率低的缺点,引入Inver-over倒异算子、贪心算子,改进近邻优化、映射算子、变异算子等策略,提出一种新的改进演化算法来求解中等规模旅行商问题(TSP).通过仿真实验,验证了该进化算法收敛速度快、求解成功率高的优点,稳定性也更好.