基于降半Γ分布函数的自适应遗传算法

Adaptive Genetic Algorith m Basedon Distributed Function of Half Γ Decline

针对遗传算法中交叉概率和变异概率难以选取的问题，提出一种新的自适应遗传算法：利用降半Γ分布函数对交叉概率和变异概率进行自适应调整，使这两个参数随基因串的适合度值而变化．仿真结果表明：该算法与传统遗传算法，常规自适应遗传算法相比，有效地克服了过早收敛问题，提高了搜索效率．

An new adaptive genetic algorith m is proposed to solve the problem of choosing the prob abilities of crossover and mutation , Distuibuted function of half Γdecline is defined on the fitnessvalues of the solutions . Experimental results show that this method not only avoids the problem ofpremature convergence ,but also is more effective than standard genetic algorith m and standardadaptive genetic algorith m .