【摘要】 标准类电磁机制算法处理连续函数优化问题时存在最优参数选取和收敛速度问题.数值实验研究表明类电磁算法不具备初值敏感性,并在搜索后期算法收敛速度缓慢甚至可能出现停滞.数值实验分析指出粒子之间达成动态力平衡状态是造成算法停滞的可能原因之一,提出一种解决策略是摒弃EM算法后期搜索过程,结合变尺度法对EM算法前期搜索到的近似最优值进行二次优化.该混合计算方法将二者的优势相结合,实验结果表明新方法在保证计算实时性的同时,取得了较高的计算精度.最后,对EM算法本身构造提出一些改进意见,并初步建立用于连续函数优化的EM算法计算框架,为后续更深入的研究EM算法提供参考.更多还原

【Abstract】 When optimizing a continuous function using a standard electromagnetism-like mechanism ( EM),there are known problems,including selection of optimal parameters and convergence speed.Numerical simulations indi-cate that EM is not sensitive to initial values,but algorithm convergence is slow and may even stagnate in the latter part of a search.One of the possible causes for stagnation is the equilibrium of dynamic forces between particles.In order to improve the performance of the EM,instead of the latter search process,a quadratic optimization method was proposed.When combined with the Davidon-Fletcher-Powell ( DFP) method,it optimized the approximate op-timal results obtained by a pre-search with the EM algorithm.This hybrid method fully exploits the strengths of the EM method and the DFP method.Experimental results showed it to be more efficient and precise.Finally,some improvements were made to the construction of the EM and a framework for the EM method was established that al-lows continuous function optimization.These results provide a reference for more in-depth study of the EM algo-rithm.更多还原