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首页> 外文期刊>International Journal of Applied Mathematics & Statistics >An Improved Ant Colony Algorithm for Continuous Domain and Its Convergence Analysis
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An Improved Ant Colony Algorithm for Continuous Domain and Its Convergence Analysis

机译：改进的连续域蚁群算法及其收敛性分析

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摘要

In order to solve the main problems of continuous domain ant colony optimization algorithm, namely the problems of large complexity and large number of iterations, this paper proposed an improved ant colony algorithm of fine mining solution space; this algorithm can effectively achieve global quick search. The new algorithm's specific steps were presented and its convergence was proved. Simulation experiments were carried out to compare in details among the improved ant colony algorithm, existing continuous domain ant colony algorithm and other intelligent optimization algorithms. Simulation results showed that: convergence speed, global search performance and optimal performance of improved ant colony algorithm were improved significantly. A theoretical basis was provided for improving the performance of continuous domain ant colony optimization algorithm.
机译：为了解决连续域蚁群优化算法的主要问题，即复杂度大和迭代次数大的问题，提出了一种改进的精细挖掘解空间的蚁群算法。该算法可以有效地实现全局快速搜索。提出了新算法的具体步骤，并证明了其收敛性。进行了仿真实验，详细比较了改进的蚁群算法，现有的连续域蚁群算法和其他智能优化算法。仿真结果表明：改进的蚁群算法的收敛速度，全局搜索性能和最优性能都有明显提高。为提高连续域蚁群优化算法的性能提供了理论依据。

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