【摘要】 为了提高基于距离测度的自适应遗传退火算法的收敛概率和收敛速度,提出了一种改进的算法,定义基于距离密集度和适应度的自适应变异概率,采用改进的算术交叉操作和模拟退火操作,并在群体趋于一致时保留最优个体,重新产生其他新个体。利用改进的距离测度实数编码遗传算法对带边界约束函数优化问题进行了仿真计算,结果表明该算法收敛概率较高,收敛速度快,是一种有效的算法。更多还原

【Abstract】 In order to increase convergence probability and evolving speed of the adaptive genetic annealing algorithm based on distance measurement,an improved algorithm was proposed.The algorithm defined the mutation probability according to distance density and fitness,adopted improved crossover and simulated annealing operation.In addition,when population tended to be uniform,it reserved the best individual and reproduced other individuals.Applying the improved real-coded genetic algorithm based on distance measurement to function optimization problem with boundary constraints,the simulative results show that the improved algorithm is more effective in realizing the high convergence probability and rapid evolving speed.更多还原