Using the genetic algorithm to calculate the extremum of a objective function. Compared with the traditional optimization methods (enumeration, heuristics, etc.), genetic algorithms take the biological evolution as the prototype, which has good convergence. It has the advantages of less computational time and high robustness when calculating the precision requirements .

Filename	Size	Update
遗传算法\best.m	565	2017-12-13
遗传算法\binary2decimal.m	401	2017-12-13
遗传算法\cal_objvalue.m	432	2017-12-13
遗传算法\crossover.m	607	2017-12-13
遗传算法\initpop.m	349	2017-12-13
遗传算法\main.asv	1028	2018-01-03
遗传算法\main.m	1024	2018-01-02
遗传算法\mutation.m	657	2017-12-13
遗传算法\selection.m	673	2017-12-13
遗传算法	0	2018-01-03

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