文件名称:Matlab代码
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遗传算法
1、评估每条染色体所对应个体的适应度
2、遵照适应度越高,选择概率越大的原则,从种群中选择两个个体作为父方和母方
3、抽取父母双方的染色体,进行交叉,产生子代
4、对子代的染色体进行变异
5、重复2,3,4步骤,直到新种群的产生。结束循环。(1. Evaluate the fitness of each chromosome.
2. Following the principle of higher fitness and greater probability of selection, two individuals are selected from the population as the parent and the parent.
3. Extract the chromosomes of both parents and cross them to produce offspring.
4. Mutation of the chromosomes of the progeny
5, repeat 2, 3, 4 steps until the new population is born. End the cycle.)
1、评估每条染色体所对应个体的适应度
2、遵照适应度越高,选择概率越大的原则,从种群中选择两个个体作为父方和母方
3、抽取父母双方的染色体,进行交叉,产生子代
4、对子代的染色体进行变异
5、重复2,3,4步骤,直到新种群的产生。结束循环。(1. Evaluate the fitness of each chromosome.
2. Following the principle of higher fitness and greater probability of selection, two individuals are selected from the population as the parent and the parent.
3. Extract the chromosomes of both parents and cross them to produce offspring.
4. Mutation of the chromosomes of the progeny
5, repeat 2, 3, 4 steps until the new population is born. End the cycle.)
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下载文件列表
文件名 | 大小 | 更新时间 |
---|---|---|
Matlab代码 | 0 | 2018-04-13 |
Matlab代码\crossover.m | 812 | 2018-03-22 |
Matlab代码\fitness.m | 883 | 2018-04-07 |
Matlab代码\genetic_algorithm.m | 2183 | 2018-03-23 |
Matlab代码\init.m | 374 | 2018-03-21 |
Matlab代码\main.m | 628 | 2018-03-23 |
Matlab代码\mutation.m | 542 | 2018-03-21 |
Matlab代码\plotGA.m | 183 | 2018-03-23 |
Matlab代码\plotIterative.m | 627 | 2018-04-07 |
Matlab代码\rank.m | 2160 | 2018-03-22 |
Matlab代码\Schaffer.m | 135 | 2018-03-23 |
Matlab代码\selection.m | 1906 | 2018-03-23 |
Matlab代码\target.m | 126 | 2018-03-23 |
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