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Discussion of the Three Problems in Genetic Algorithm with Chromosome Differentiation

机译:染色体微分遗传算法中三个问题的探讨

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Bandyopadhyay and Pal proposed an improved genetic search strategy, GACD (Genetic Algorithm with Chromosome Differentiation), involving partitioning the chromosomes into two classes, and defining a restricted form of the crossover operator between the two classes. The GACD can be applied to many multi-dimensional pattern recognition problems. However, their GACD suffered from three problems, i.e. ȁC;sampling-without-replacementȁD;, ȁC;mating-with-best-chromosomeȁD; and ȁC;the-unreachable-resultȁD;.
机译:Bandyopadhyay和Pal提出了一种改进的遗传搜索策略GACD(具有染色体差异的遗传算法),其中涉及将染色体分为两类,并定义了两类之间的交叉算子的受限形式。 GACD可以应用于许多多维模式识别问题。但是,他们的GACD遇到三个问题,即ȁC;无取代采样ȁD;,C;最佳染色体交配; D ;; C。和ȁC;无法达到的结果ȁD;

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