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针对图的多划分问题的特点 ,本文提出了一种适合于求解这一类问题的改进遗传算法 .该算法无论在编码方式、算子设计乃至算子功能的界定上 ,都与经典遗传算法有着很大差别 .实例验证 ,该算法是通用的和有效的 .它既充分利用了遗传算法全局性的搜索能力 ,又增强了遗传算法的局部搜索能力 ,明显地提高了收敛速度 .该算法的提出 ,大大减轻了用户解决具体应用问题的负担 .
Aiming at the characteristics of multi-partitioned graph, this paper proposes an improved genetic algorithm that is suitable for solving this kind of problems.The algorithm has the same advantages as classical genetic algorithm in the definition of coding method, operator design and operator function The difference between them is very high.Examples show that the algorithm is universal and effective.It not only makes full use of the global search ability of genetic algorithm but also enhances the local search ability of genetic algorithm and obviously improves the convergence speed.The proposed algorithm , Greatly reducing the burden on users to solve specific application problems.