Traveling Salesman Problem Solution Based on Subsection Shuffled Frog Leaping Algorithm
Xiaoya Guo · Jisuanji gongcheng · 2014
Because reduction of the diversity of solution causes the reduction of search speed and accuracy at the same time in the later period of search according to Traveling Saleman Problem(TSP). A Subsection Shuffled Frog Leaping Algorithm(S-SFLA) is proposed. In the initial period of search, in-over operator is used to reduce cross paths. In the latter period, the neighborhood search(individual neighborhood, local optimal area, the global optimal neighborhood) is introduced to increase the diversity of population. In the whole search process, global optimal solution of history and the local optimal solution of history are remembered to avoid circuit search, and in the process of local update, every frog has the opportunity to be updated. Experimental results show that, compared with genetic algorithm, ant colony algorithm, basic leapfrog algorithm, S-SFLA algorithm has higher precision and search speed in solving TSP problem of medium scale.