基于多样化进化策略的基因表达式编程算法

针对传统GEP(Gene Expression Programming )算法的未成熟收敛以及陷入局部最优问题，提出一种基于多样化进化策略的基因表达式编程算法(DS-GEP:Gene Expression Programming based on diversified development strategy)。该算法通过基因空间均匀分布策略，自适应地交叉和变异算子以及淘汰算子等方法，对种群给予不同的进化策略，以保持种群的多样性，从而增强算法的寻优能力。通过对函数挖掘的实验证明，多样化进化策略各个部分均对改善挖掘效率发挥了作用，提高了DS-GEP函数挖掘算法的成功率。与传统GEP算法相比较,该算法的平均成功进化代数缩短了11%，成功进化时间缩短了8%，进化成功率提高了20%。

Gene Expression Programming Based on Diversified Development Strategy

In order to reduce the rate of premature convergence and to escape from local optimum, GEP(Gene Expression Programming) based on diversified development strategy is proposed, which assigns the population with different development strategies to enhance the optimizing ability of GEP through GSBS（Gene Space Balance Strategy), ACMO（Adaptive Crossover and Mutation Operators) and obsolete operator (OBSO). Experiments on function mining show that all of strategies play roles of mining. Compared with the result of GEP. The number of average evolution generations is decreased by 11%, evolution time is decreased by 8%, and the success rate is increased by 20%.