一种求解TSP问题的改进遗传算法

TSP问题是一类经典的NP完全组合优化问题，传统的优化方法由于计算复杂性过大而难以求得全局最优解。遗传算法等智能优化算法在求解这类组合优化问题中表现出了强劲的潜力。作者利用遗传算法对TSP问题进行了研究分析，针对几组benchmark数据进行了仿真实验，在实验的基础上探索了遗传算子和遗传参数的优化设计，实验结果证明了遗传算法在解决TSP问题上的可行性和有效性。

An Improved Genetic Algorithm for TSP

Traveling Salesman Problem (TSP) is a kind of NP-complete combinatorial optimization problem, and the traditional optimization methods are difficult to solve it because of the weakness of high complexity in computation. The Intelligent Optimization Algorithms, such as Genetic Algorithm, show a powerful potential in solving these combinatorial optimization problems. This paper studies and analyzes TSP with Genetic Algorithm, and makes a series of emulational experiments aiming at benchmark data, then explores the optimization design of the operators and parameters based on the experimental data. The results indicate that Genetic Algorithm is feasible and efficient in solving TSP.