蚁群算法及其在旅行商问题中的应用

Shi-gang Cui, Shaolong Han
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引用次数: 4

摘要

随着现代化科学技术的飞速发展,高新技术得到了越来越广泛的应用。蚁群算法是仿生元启发式系统的一个新范畴,该算法采用并行计算和正反馈机制。蚁群算法具有较强的鲁棒性和易于与其他优化方法结合的特点,在各种组合优化领域得到了广泛的应用,但基本蚁群算法收敛速度慢,容易停滞,容易收敛到局部解。许多学者做了大量的努力来改善这些弱点,但研究仍有待改进。阐述了蚁群算法和TSP问题的基本原理、模型、优缺点,提出了蚁群算法在求解旅行商问题中的具体实现过程,并通过仿真验证了算法的可行性。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Ant Colony Algorithm and Its Application in Solving the Traveling Salesman Problem
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.
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