遗传算法课件PPT.pptxVIP

遗传算法;目录 CONTENTS;;;TITLE 01;;遗传算法步骤;1;;遗传算法;;;;time_t now; # include math. one = mem; ++first; double round(double number) gene[i] = r8_uniform_ab ( lbound, ubound, seed ); lbound = population[i]. if ( NVARS 2 ) cur_best = 0; crossover ( seed ); 以编码空间代替问题参数空间，从代表问题可能有潜在解集的一个种群出发，按照生物进化过程中适者生存、优胜略汰的原理，以适应度作为评价个体优劣的依据，重复使用选择、交叉、变异算子作用于群体，使之不断进化，逐渐接近最优解 for ( mem = 1; mem POPSIZE; mem++ ) mutate ( seed ); fitness = worst ) void crossover ( int seed ) //交叉运算;for ( mem = 1; mem POPSIZE; mem++ ) setw(14) avg void elitist ( ) seed = seed + i4_huge; x[i+1] = population[member]. } cfitness = population[mem-1]. fitness population[mem]. double cfitness; rfitness = 0; end?for double lbound; for ( mem = 0; mem POPSIZE; mem++ ) cout \n; if ( seed == 0 ){;Procedures??GA：???伪代码 begin ???????initialize?P(0); // (1)初始化? ???????t?=?0;????????????? //t是进化的代数，一代、二代、三代... ???????while(t?=?T)?do //T是最大进化代数; ??????????????for?i?=?1?to?M??do???? //M是初始种群的个体数,随机生成M个个体作为初始群体???P（t）； ?????????????????????Evaluate?fitness?of?P(t);?? // (2) 个体评价?计算P（t）中各个个体的适应度值； ??????????????end?for ??????????????for?i?=?1?to?M??do ?????????????????????Select?operation?to?P(t);?? // (3) 选择运算?将选择算子作用于群体； ??????????????end?for ??????????????for?i?=?1?to?M/2??do ?????????????????????Crossover?operation?to?P(t);? // (4) 将交叉算子作用于群体交叉运算?; ???????????????end?for ??????????????for?i?=?1?to?M??do ?????????????????????Mutation?operation?to?P(t);?? // (5) 将变异算子作用于群体变异运算?; ??????????????end?for ??????????????for?i?=?1?to?M??do ?????????????????????P(t+1)?=?P(t);?????? // (6) 通过以上运算