计算机科学与探索2025，Vol.19Issue(6)：1522-1539,18.DOI:10.3778/j.issn.1673-9418.2407113
融合独立思维与局部逃逸的头脑风暴优化算法
Brain Storm Optimization Algorithm Integrating Independent Thinking and Local Escaping
摘要
Abstract
The brain storm optimization algorithm(BSO)is a swarm intelligence optimization algorithm proposed to simulate human brain thinking activities.Aiming at the problems of poor accuracy and weak optimization ability of traditional brainstorming optimization algorithms,which are prone to falling into local optima,an improved brain storm optimization algorithm(IBSO)that integrates independent thinking and local escaping is proposed.Firstly,an independent thinking strategy is proposed,which adds a threshold to determine whether to execute the independent thinking strategy when the algorithm is stuck in a local optimal solution.When the algorithm falls into a local optimum and cannot obtain a better solution,it will use an independent thinking strategy to find a new position,assisting the algorithm in seeking a better solution to escape from the local optimum.Secondly,the local escaping operator(LEO)strategy is adopted to enhance the algo-rithm's global exploration capability and improve its search efficiency.Optimization performance of IBSO algorithm is tested using CEC2014 benchmark test function and CEC2020 benchmark test function,and comparative experiments with 8 optimization algorithms are conducted.The results indicate that the improved algorithm has stronger optimization ability,higher stability,and global search capability.Finally,the latest engineering problem evaluation indicators are used to conduct testing experiments on two engineering problems,namely the design of a three bar truss and the design of tension/compression springs,further verifying the practicality of the IBSO algorithm in engineering problems.关键词
头脑风暴优化算法/局部逃逸策略/基准测试函数/工程问题Key words
brain storm optimization algorithm/local escaping operator/benchmark function/engineering problem分类
信息技术与安全科学引用本文复制引用
贾鹤鸣,饶洪华,吴迪,薛博文,文昌盛,李永超..融合独立思维与局部逃逸的头脑风暴优化算法[J].计算机科学与探索,2025,19(6):1522-1539,18.基金项目
全国教育科学规划教育部重点课题(DIA220374). This work was supported by the National Education Science Planning Key Project of the Ministry of Education(DIA220374). （DIA220374）
