GA is a method of searching for the optimal solution by simulating the natural evolutionary process. It is often used in CRN resource optimization. GA starts with a popu-lation that represents a potential set of solutions to a prob-lem, while a population consists of a finite number of indi-viduals (called phenotype) encoded by genes. Each individ-ual is actually an entity with a chromosome(called geno-type). Chromosome as a major carrier of genetic material, that is, a collection of multiple genes.

Filename	Size	Update
GA多目标约束问题\crossover.m	345	2017-05-14
GA多目标约束问题\decode_x1.m	197	2017-05-14
GA多目标约束问题\decode_x2.m	196	2017-05-14
GA多目标约束问题\main.m	1298	2017-05-14
GA多目标约束问题\mutation.m	324	2017-05-14
GA多目标约束问题\seclection.m	414	2017-05-14
GA多目标约束问题	0	2018-01-01

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