一种多种群二进制算术优化算法及其应用  

Multi-swarm binary arithmetic optimization algorithm and its application

作　　者：王若宾[1,2] 耿芳东 王佳伟 徐琳 段建勇[1] Wang Ruobin;Geng Fangdong;Wang Jiawei;Xu Lin;Duan Jianyong(School of Information Science&Technology,North China University of Technology,Beijing 100144,China;Beijing Urban Governance Research Center,North China University of Technology,Beijing 100144,China;State Key Laboratory of Traction Power,Southwest Jiaotong University,Chengdu 610031,China;STEM,University of South Australia,Adelaide 5095,Australia)

机构地区：[1]北方工业大学信息学院,北京100144 [2]北方工业大学北京城市治理研究基地,北京100144 [3]西南交通大学轨道交通运载系统全国重点实验室,成都610031 [4]南澳大学科学技术工程与数学学部,澳大利亚阿德莱德5095

出　　处：《计算机应用研究》2024年第12期3664-3670,共7页Application Research of Computers

基　　金：国家自然科学基金资助项目(61972003)。

摘　　要：针对算术优化算法(AOA)无法对离散二进制型问题进行优化的局限,提出一种使用sigmoid函数变体实现的离散二进制算术优化算法(BAOA_S),解决了原始算法无法用于离散二进制变量优化的问题。进一步提出一种基于突变策略实现的多种群二进制算术优化算法(multi-swarm binary arithmetic optimization algorithms,MS-BAOA)。该算法将原始种群划分为多个子种群,子种群间通过通信策略进行交流,并使用突变策略进一步增强种群多样性,克服了BAOA_S无法跳出局部最优解的缺陷。基于CEC2013基准函数将MS-BAOA与BAOA_S、二进制粒子群算法(binary particle swarm optimization algorithm,BPSO)、二进制灰狼优化算法(binary gray wolf optimizer,BGWO)、二进制鱼群迁徙算法(binary fish migration optimization algorithm,BFMO)以及二进制均衡优化器(binary equilibrium optimizer,BiEO)进行了对比,实验结果显示MS-BAOA总体上优于对比算法。将MS-BAOA应用于配电网故障区段定位中,实验结果显示该算法能够对配电网单点故障以及多点故障实现快速精准定位,进一步验证了该算法的实用性。To address the issue that AOA is not applicable to discrete binary type optimization problems,this paper proposed a novel algorithm:the discrete binary arithmetic optimization algorithm employing a variant of the sigmoid function(BAOA_S).This algorithm was capable of overcoming the challenge of the original AOA’s inability to optimize discrete binary variables.In addition,this paper proposed a multi-swarm binary arithmetic optimization algorithm(MS-BAOA)employing a mutation stra-tegy to divide the original population into multiple sub-swarms that communicated with one another through the use of specific communication strategies.The mutation strategy was then employed to enhance population diversity,addressing a weakness of the BAOA_S algorithm:the challenge of escaping local optimal solutions.This paper evaluated MS-BAOA against BAOA_S,BPSO,BGWO,BFMO,and BiEO based on the CEC2013 benchmark function.And the experimental results show that MS-BAOA is generally superior to the other algorithms.Furthermore,this paper applied MS-BAOA to solve the fault localization problem of distribution networks.And the experimental results show that the algorithm can realize the fast and accurate localization of single-point faults and multi-point faults in distribution networks further verifying the effectiveness of the algorithm.

关 键 词：算术优化算法 离散二进制 多种群 配电网 故障定位 

分 类 号：TP301.6[自动化与计算机技术—计算机系统结构]