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中文摘要：
针对基本差分进化算法的缺陷,融入指数递增交叉算子以增加算法的收敛速度.当算法陷入早熟后,对最优个体和随机选取的个体采用随机扰动的变异策略,帮助其跳出局部极值.数值仿真实验表明,该算法的收敛速度和精度都明显优于仅带有指数递增交叉算子的差分进化算法和仅带有随机扰动变异策略的差分进化算法.
英文摘要：
For the basic differential evolutionary algorithm＇s drawback, merging exponent increased crossover operator improves convergence rate. After algorithm fall into premature, the best individual and randomly selecting individuals are mutated by random disturbance strategy to escape local extremes. Numerical simulations show that the proposed algorithm is better than the DE algorithm only with exponent increased crossover operator or the DE algorithm only with random disturbance mutation strategy in convergence rate and accuracy.
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同项目期刊论文
Modified Multi-Objective Particle Swarm Optimization Algorithm for Multi-objective Optimization Prob
Modified differential evolution algorithm of constrained nonlinear mixed integer programming problem
PSO algorithm with chaos and gene density mutation for solving nonlinear zero-one integer programmin
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