A new imperialist competitive algorithm with spiral rising mechanism for solving path optimization problems

被引：0

作者：

Li X. ^{[1
]}

Chen J. ^{[1
]}

Sun L. ^{[1
]}

Li J. ^{[1
]}

机构：

[1] School of Automation Engineering, Northeast Electric Power University, Jilin

来源：

PeerJ Computer Science | 2022年 / 8卷

基金：

中国国家自然科学基金;

关键词：

Global optimization ability; Imperialist competitive algorithm; Intelligent optimization algorithm; Path planning problem;

D O I：

10.7717/PEERJ-CS.1075

中图分类号：

学科分类号：

摘要：

Intelligent optimization algorithms have now become important means for solving global optimization problems. The imperialist competitive algorithm (ICA) is a nature-inspired meta-heuristic algorithm that imitates social behavior. ICA has been widely used in optimization problems, however, ICA tends to fall into a local optimal solution because of its fast convergence speed, which may lead to premature convergence when solving optimization problems. To solve these problems, a new improved ICA algorithm is proposed. Based on the original ICA algorithm, the theory of spiral rising is introduced to enlarge the search space and enhance the global search ability of the algorithm based on ensuring the necessary speed of convergence. In this paper, the improved optimization algorithm is applied to 19 classical benchmark functions, and the improved ICA is applied to the robot path optimization problems to solve the optimal path. The improved ICA algorithm improves the optimization ability and algorithm stability © Copyright 2022 Li et al

引用

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