蚁狮优化算法研究综述  

A Review of Ant Lion Optimization Algorithms Research

作　　者：胡城 蔡延光[1] 黄嘉铖 曾庆丰 HU Cheng;CAI Yanguang;HUANG Jiacheng;ZENG Qingfeng(College of Automation,Guangdong University of Technology,Guangzhou 510006,China)

机构地区：[1]广东工业大学自动化学院,广东广州510006

出　　处：《自动化与信息工程》2024年第3期1-10,15,共11页Automation & Information Engineering

基　　金：广东省科技计划项目(2016A050502060,2020B1010010005);广州市科技计划项目(202206010011,2023B03J1339)。

摘　　要：蚁狮优化(ALO)算法是通过模拟自然界中蚁狮捕食蚂蚁的狩猎机制而提出的一种新型元启发式算法,广泛应用于各种优化问题,具有全局寻优能力强、收敛精度高、简单易实现等特点。首先,简述ALO算法的原理及流程;然后,阐述ALO算法的多种变体;接着,介绍ALO算法在工程设计、人工智能、计算机科学、电力系统优化、控制系统等领域的应用;最后,对ALO算法进行总结,并提出建议和未来可能的研究方向。The ant lion optimization(ALO)algorithm is a novel metaheuristic algorithm proposed by simulating the hunting mechanism of ant lions in nature.It is widely used in various optimization problems and has the characteristics of strong global optimization ability,high convergence accuracy,and easy implementation.Firstly,briefly describe the principle and process of ALO algorithm;Then,elaborate on the various variants of the ALO algorithm;Next,introduce the applications of ALO algorithm in engineering design,artificial intelligence,computer science,power system optimization,control systems,and other fields;Finally,summarize the ALO algorithm and propose suggestions and possible future research directions.

关 键 词：蚁狮优化算法 元启发式算法 综述 

分 类 号：TP301.6[自动化与计算机技术—计算机系统结构]