求解全局优化问题的SCA-VPPSO算法及其应用  

A Novel SCA-VPPSO Algorithm for Global Optimization Problems and Its Engineering Application

作　　者：曹琦 程雷平 徐成 方宁[3] CAO Qi;CHENG Lei-ping;XU Cheng;FANG Ning(Longyan Tobacco Industrial Co.,Ltd.,Longyan 364021,China;Wuhu Cigarette Factory of China Tobacco Anhui Industrial Co.,Ltd.,Wuhu 241000,China;School of Electronic and Information Engineering,Beihang University,Beijing 100191,China)

机构地区：[1]龙岩烟草工业有限责任公司,福建龙岩364021 [2]安徽中烟工业有限责任公司芜湖卷烟厂,安徽芜湖241000 [3]北京航空航天大学电子信息工程学院,北京100191

出　　处：《计算机技术与发展》2024年第9期182-187,共6页Computer Technology and Development

基　　金：国家自然科学基金(61871010)。

摘　　要：正余弦算法和速度暂停粒子群算法是两个优秀的元启发式算法,用于解决连续全局优化问题。在解决实际问题中,它们始终面临着跳出局部极小的问题。为此,基于二者,提出了一种新的混合搜索算法,称为SCA-VPPSO算法。该算法以速度暂停粒子群算法的搜索框架为基础,将正余弦搜索算子从原先的全维度更新策略转变为部分维度更新策略,并将之用于开发探索上,与速度暂停粒子群算法中的局部搜索行为进行了融合,形成双模式局部探索模式。混合后的SCA-VPPSO算法能够更加有效地平衡局部利用和全局探索,从而增强算法跳出局部最小的能力并获得更好的结果。所提算法与正余弦算法、速度暂停粒子群算法和2个近期发表的优秀算法在CEC2019测试集和一个工程实际应用上进行了性能分析,结果表明所提算法的优化性能有显著提高,扩展了算法的应用范围,为元启发式算法的发展提供了新的混合搜索模式。The sine cosine algorithm and the velocity paused particle swarm optimization algorithm are two highly effective metaheuristic algorithms employed for addressing continuous global optimization problems.However,when applied to practical scenarios,these algorithms consistently encounter the challenge of escaping local minima.Therefore,we propose the SCA-VPPSO algorithm,a novel hybrid search algorithm designed for addressing continuous global optimization problems.Based on the search framework of velocity paused particle swarm algorithm,the sine-cosine search operator is transformed from the original full-dimensional update strategy to a partial dimension update strategy,which is used in development and exploration,and integrates with the local search behavior of velocity paused particle swarm algorithm to form a two-mode local exploration mode.The hybrid SCA-VPPSO algorithm can balance local utilization and global exploration more effectively,thus enhancing the ability of the algorithm to escape the local minimum and obtain better results.The performance evaluation of the proposed algorithm,in conjunction with the sine cosine algorithm,velocity paused particle swarm optimization algorithm,and two recently published exemplary algorithms,was carried out on both the CEC2019 test set and an engineering practical application.The findings demonstrated a notable enhancement in the optimization performance of the proposed algorithm,thereby broadening its potential applications and presenting a novel hybrid search approach for the advancement of metaheuristic algorithms.

关 键 词：全局优化 粒子群算法 正余弦算法 元启发式算法 工程应用 

分 类 号：TP301[自动化与计算机技术—计算机系统结构]