An improved floating-point coded genetic algorithm controlled by information entropy is presented to solve the constrained optimization problems based on the quasi-exact penalty function.
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在用准精确惩罚函数处理约束优化问题的基础上,提出一种基于浮点数编码机制的信息熵控制多种群遗传算法。
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