On Convergence of Pigeon Inspired Optimization Algorithm

Gangireddy Sushnigdha, Aeidapu Mahesh
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Abstract

The pigeon inspired optimization (PIO) is a metaheuristic algorithm which finds an optimal solution in the complex search spaces using homing behavior of pigeons. PIO algorithm has been applied to solve various optimization problems in different domains and is empirically shown to perform well. However, the convergence of this algorithm has not been established analytically in the literature. In this paper, the update equations of PIO algorithm are regarded as a discrete time-varying system and its convergence is analysed. This paper attempts to establish the convergence of PIO algorithm using two methods. The first method uses the state transition matrix approach and the second method is based on showing the convergence using the solution of linear discrete time-varying systems. Further, the appropriate choice of the parameter in PIO algorithm and its influence on the convergence of the algorithm is also discussed.
鸽子启发优化算法的收敛性研究
鸽子启发优化算法是利用鸽子的归巢行为在复杂搜索空间中寻找最优解的一种元启发式算法。PIO算法已被应用于解决不同领域的各种优化问题,并被经验证明具有良好的性能。然而,该算法的收敛性在文献中尚未得到解析性证明。本文将PIO算法的更新方程视为一个离散时变系统,分析了其收敛性。本文尝试用两种方法来证明PIO算法的收敛性。第一种方法使用状态转移矩阵方法,第二种方法基于使用线性离散时变系统的解来显示收敛性。进一步讨论了PIO算法中参数的合理选择及其对算法收敛性的影响。
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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