Adaptive Greedy GA Algorithm for TSP
用于TSP的自适应贪婪GA算法

TSP is a typical combinatorial optimization problem, and many real life problems can attributed to the TSP.GA is a typical optimization algorithm. Analyzing GA's important points,a adaptive greedy GA was proposed to solve TSP. Definitions and theorems on adaptive fitness function ensure the correctness of the algorithm. Algorithm does not prematurely fall into local optimum because of average replication method for select operations. Algorithm can be efficiently converged by establishing bidirectional ring greed insert operator based on Hamiltonian two-way loop circuit for cross operation. Finally, the calculation and analysis of the example and the comparison with the traditional GA algorithm show that the proposed GA algorithm can play better role in TSP study.