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Description: 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)
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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
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-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 ====== ================================================== =================
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Size: 2048 |
Author: 王晶 |
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Description: 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
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Size: 3072 |
Author: 何敏 |
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