Design and expending of Adaptive Neighborhood Searching Algorithm for TSP

TSP is a classical platform for testing performance of algorithms in combinatorial optimization fields.This paper brings forward an Adaptive Neighborhood Searching Algorithm(ANSA).The new algorithm simplifies the complication of TSP problem by setting neighborhood area for each city,and an adaptive neighborhood searching operator based on satisfaction and activity is designed,aiming at gaining super performance in the speed of local optimization and convergence effect.In order to combine the efficiency of local optimization and robustness of GA,a combinatorial optimization algorithm is introduced.The simulation results of eil75,CHN144 and some problems from TSP library indicate that the over-all properties of the proposed scheme are superior to that of some current algorithms.