摘要
针对标准电磁场优化算法容易陷入局部极值点、收敛精度差等问题,提出了一种多策略引导的电磁场优化算法。算法中粒子受到三种不同来源的引斥力,在迭代过程中通过计算每种移动策略的临代电差、累计电差和综合电差来决定粒子的引导方式,并通过概率变异算法来避免陷入局部最优解。在经典的基准测试函数上,对新算法与其他算法的测试结果比较进行分析,结果表明该算法具有更高的求解精度和更快的计算速度。
A multi-strategy guided electromagnetic field optimization algorithm happens to aim at the problem that the standard electromagnetic field optimization algorithm is easy to fall into local extremum and poor convergence precision.In the algorithm,the particles suffer the repulsive force of three different sources.In the iterative process,calculating the generational electrical difference,the cumulative electrical difference and the integrated electrical difference of each mobile strategy,which determines the particle conduction mode and avoids falling into the trap with the probability mutation algorithm.On the classic benchmark function,analysis of the comparison between the new algorithm and other algorithms shows that the algorithm has higher accuracy and faster calculation speed.
作者
陈斌
马良
刘勇
Chen Bin;Ma Liang;Liu Yong(Business School,University of Shanghai for Science&Technology,Shanghai 200093,China)
出处
《计算机应用研究》
CSCD
北大核心
2020年第7期2011-2015,2036,共6页
Application Research of Computers
基金
国家教育部人文社会科学研究规划基金资助项目(16YJA630037)
上海市“科技创新行动计划”软科学研究重点项目(18692110500)
上海市高原科学建设项目(第二期)。
关键词
电磁场优化算法
多策略
引斥力
最优化
electromagnetic field optimization algorithm
multi-strategy
repulsive force
optimization
