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实现了蚁群算法求解TSP问题。注释详细 function[R_best,L_best,L_ave,Shortest_Route,Shortest_Length]=ACATSP(C,NC_max,m,Alpha,Beta,Rho,Q) ------------------------------------------------------------------------- 主要符号说明 C n个城市的坐标,n×2的矩阵 NC_max最大迭代次数 m蚂蚁个数 Alpha表征信息素重要程度的参数 Beta表征启发式因子重要程度的参数 Rho信息素蒸发系数 Q信息素增加强度系数 R_best各代最佳路线 L_best各代最佳路线的长度 ========================================================================= -Ant Colony Algorithm for the realization of the TSP problem. Notes the detailed function [R_best, L_best, L_ave, Shortest_Route, Shortest_Length] = ACATSP (C, NC_max, m, Alpha, Beta, Rho, Q) ------------------------------------------------------------------- The main symbol------ C n that cities coordinates, n × 2 matrix NC_max the largest number of iterations m the number of Alpha ant pheromones characterized the importance of the parameters Beta factor heuristic importance of characterization of the parameters Rho evaporation coefficient of pheromone pheromone Q increase in intensity coefficient R_best best route generations generations L_best the length of the best route ====== ================================================== =================
Update : 2025-03-07 Size : 2kb Publisher : 王晶

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用蚁群算法求解tsp问题,以中国31个城市的坐标数据为案例-Problem solving tsp with ant colony algorithm to coordinate data 31 cities in China as a case
Update : 2025-03-07 Size : 3kb Publisher : 何敏
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