关键词: 组合优化问题, 旅行商问题（TSP）, 混合蛙跳算法, 概率, TSPLIB

Abstract: According to the TSP character, an improved shuffled frog-leaping algorithm is designed. The algorithm improves the child population frog individual optimization way, not just the worst individual optimization. This way can improve the convergent speed of the algorithm effectively. In order to enhance the ability of searching, “guide optimal” probability and “guide suboptimal” probability are put forward. The “guide optimal” probability represents the global optimum solution probability that the individual reversal depends on. The “guide suboptimal” probability represents the subpopulation optimum solution probability that the individual reversal depends on. Through experiments to multiple problems of the TSPLIB, the results show that the algorithm is feasible and effective.

Key words: combinatorial optimization problem, Traveling Salesman Problem（TSP）, shuffled frog-leaping algorithm, probability, TSPLIB