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提出了一种改进的差分进化算法,用于求解约束优化问题.该算法首先利用佳点集方法产生初始个体以维持种群的多样性.在进化过程中,根据种群中可行解的比例自适应地选取不同的变异策略和交叉操作,增强了算法的勘探和开采能力.利用几个标准的Benchmark问题进行了测试.实验结果表明,该算法能处理不同的约束优化问题.
An improved differential evolution algorithm is proposed to solve the constrained optimization problem.The algorithm first uses the good point set method to generate the initial individual to maintain the diversity of the population.In the evolutionary process, according to the proportion of feasible solutions in the population adaptively Different mutation strategies and crossover operations are selected to enhance the exploration and exploitation ability of the algorithm.The test is conducted with several standard Benchmark problems.The experimental results show that the algorithm can deal with different constrained optimization problems.