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作 者:林之博 刘媛华[1] LIN Zhi-bo;LIU Yuan-hua(Business School,University of Shanghai for Science and Technology,Shanghai 200093,China)
出 处:《小型微型计算机系统》2021年第8期1668-1674,共7页Journal of Chinese Computer Systems
基 金:国家自然科学基金项目(11505114)资助。
摘 要:混沌优化算法是一种可用于求解复杂连续函数极值的智能优化算法,相对经典优化算法如遗传、模拟退火、蚁群算法等具有更强的全局搜索能力.但现有混沌优化算法存在边缘游走现象,削弱了混沌优化算法的优势且求解能力有限.故首先改进设计了分片Lorenz混沌模型,通过仿真实验验证该模型具有优于Logistic系列混沌模型的搜索均匀度与鲁棒性;其次围绕该模型,利用优序堆栈产生修正解规避褶皱局部最优,并构造变密度振荡搜索法则,设计了一种新型混沌优化算法.通过多轮低、中等复杂连续函数的极值求解实验,证明了新算法能在更短时间内以满意概率找出复杂连续函数极值优化问题的全局最优解.该算法综合性能优于对比组算法,达到预期的要求.Chaos optimization algorithm is a kind of intelligent optimization algorithm which can be used to solve the extreme value of complex continuous function.Compared with the classical optimization algorithms such as genetic algorithm,simulated annealing algorithm and ant colony algorithm,it has stronger global search ability.However,the existing chaos optimization algorithm has the phenomenon of edge wandering,which weakens the advantage of chaos optimization algorithm,and its solving ability is limited.Therefore,firstly,the piecewise Lorenz chaotic model is improved and designed,and the simulation results show that the model has better search uniformity and robustness than the logistic chaotic series model;secondly,base on the model,the modified solution is generated by the optimal order stack to avoid the local optimum of folds,and the variable density oscillation search rule is constructed to design a new chaotic optimization algorithm.It is proved that the new algorithm can find the global optimal solution of the extremum optimization problem of the complex continuous function with satisfactory probability in a short time through the multi round extreme value solving experiments of various dimensional complex continuous functions.The comprehensive performance of the algorithm is better than that of the contrast group algorithm,and meets the expected requirements.
关 键 词:混沌映射系统 启发式算法 模拟振荡 单目标优化 多维极值优化
分 类 号:TP399[自动化与计算机技术—计算机应用技术]
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