为获得运行过程中对搜索空间勘探和开采的平衡 ,该文提出了一种基于种群熵估计的参数自适应遗传算法。该算法每一进化代的新种群由保留、繁殖和随机 3部分子种群组成 ,其数量则由相应的参数进行控制。通过引入种群熵的概念对种群内个体的多样性进行度量并使用一种简单的方法对其进行估计以确定各控制参数 ,该算法实现了参数的自适应调节。试验结果表明该算法能够有效协调勘探和开采 ,在处理复杂问题时表现出较高的性能 In order to obtain the balance of exploration and exploitation of search space during operation, a genetic parameter adaptive genetic algorithm based on population entropy estimation is proposed. The new population of each evolutionary generation of the algorithm consists of three subpopulations of conservation, breeding and randomization, and the number is controlled by the corresponding parameters. By introducing the concept of population entropy, the diversity of individuals in the population is measured and estimated using a simple method to determine the control parameters. The algorithm realizes the adaptive adjustment of the parameters. The experimental results show that this algorithm can effectively coordinate exploration and exploitation, and show high performance when dealing with complex problems