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Ant Colony Algorithm and Its Application in Solving the Traveling Salesman Problem

机译:蚁群算法及其在求解旅行商问题中的应用

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With the modernization of the rapid development of science and technology, high technology has been more and more widely applied. Ant colony algorithm is a novel category of bionic meta-heuristic system and parallel computation and positive feedback mechanism are adopted in this algorithm. Ant colony algorithm, which has strong robustness and is easy to combine with other methods in optimization, has wide application in various combined optimization fields, but the basic ant colony algorithm is of slow convergence and easy to stagnation and easily converges to local solutions. many scholars did a lot of effort to improve these weaknesses, but the research still needs improving. This paper expounds the basic principle, model, advantages and disadvantages of ant colony algorithm and the TSP problem, the concrete realization process of ant colony algorithm is put forward in solving traveling salesman problem and the simulation shows that solution is feasible.
机译:随着科学技术的飞速发展,高科技已得到越来越广泛的应用。蚁群算法是仿生元启发式系统的一种新类型,该算法采用并行计算和正反馈机制。蚁群算法具有很强的鲁棒性,并且易于与其他方法进行优化组合,在各种组合优化领域中都有广泛的应用,但是基本的蚁群算法收敛速度慢,容易停滞并且易于收敛到局部解。许多学者为改善这些弱点付出了很多努力,但研究仍需改进。阐述了蚁群算法的基本原理,模型,优缺点以及TSP问题,提出了蚁群算法解决旅行商问题的具体实现过程,并通过仿真证明了可行的解决方案。

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