A multiple ant colonies optimization algorithm based on immunity for solving TSP

Hongquan Xue, Peng Zhang, Lin Yang
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引用次数: 7

Abstract

The traveling salesman problem (TSP) is a wellknown NP-hard problem and extensively studied problems in combinatorial optimization. Ant colony optimization algorithm (ACOA) has been used to solve many optimization problems in various fields of engineering. In this paper, a new algorithm was presented for solving TSP using ACOA based on immunity and multiple ant colonies. The new algorithm was tested on benchmark problems from TSPLIB and the test results were presented. The experimental results show that the new algorithm effectively relieves the tensions such as the premature, the convergence and the stagnation.
基于免疫的多蚁群优化算法求解TSP
旅行商问题(TSP)是组合优化中一个著名的np困难问题,也是被广泛研究的问题。蚁群优化算法(ACOA)已被用于解决工程各个领域的许多优化问题。本文提出了一种基于免疫和多蚁群的ACOA求解TSP的新算法。在TSPLIB的基准问题上对新算法进行了测试,并给出了测试结果。实验结果表明,新算法有效地缓解了算法的过早性、收敛性和滞后性等问题。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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