基因表达式编程种群多样性自适应调控算法

为了解决基因表达式编程GEP种群多样性控制问题，提出了一种新的带权种群多样性的自适应调控方法。设计了带权的种群多样性测度方法，详细分析了选择、交叉及变异算子对种群多样性的影响。提出了初始种群的多样化算法DAIP，以保证初始种群多样性的最大化。设计了自适应的交叉和变异算子，提出了种群多样性自适应调控算法APDTA，使种群在进化过程中维持合适的种群多样性，进而提高进化效率。实验验证了APDTA的有效性。

Adaptive Population Diversity Tuning Algorithm for Gene Expression Programming

To cope with the problem of controlling population diversity in gene expression programming (GEP), an adaptive population diversity tuning algorithm is proposed. A weighted measurement for population diversity is designed. The impact in terms of selection, crossover, and mutation operators on population diversity is analyzed in detail. A diversity algorithm for initial population (DAIP) maximizing the initial population diversity is proposed as well. Aiming to appropriately maintain the population diversity and achieve high evolution efficiency, adaptive crossover and mutation operations are developed and an adaptive population diversity tuning algorithm (APDTA) is developed. Experiments show that APDTA is efficient and effective.