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Adaptive Evolutionary Genetic Algorithms on a Class of Combinatorial Optimization Problems

机译:一类组合优化问题的自适应进化遗传算法

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This paper investigates an adaptive evolutionary genetic algorithm on combinatorial optimization problem, where the solution space can be organized in form of a subset tree. A kind of genetic gene uniform encode scheme and adaptive evolution idea are used before proceeding crossover operation, and crossover is achieved between the current and previous generations individual. The orthogonal table approach is utilized to produce initial population, which can satisfy the multiplicity of the initial population. Two examples are provided to illustrate the effectiveness of the proposed methods.
机译:本文研究了组合优化问题的自适应进化遗传算法,其中解决方案可以以子集树的形式组织。在进行交叉操作之前使用一种遗传基因统一编码方案和自适应演化思路,并且在当前和之前的代文中实现交叉。正交表方法用于产生初始群体,其可以满足初始群体的多重性。提供了两个示例以说明所提出的方法的有效性。

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