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A Novel Genetic Algorithm for Degree-Constrained Minimum Spanning Tree Problem

机译:一种新型遗传算法,用于学位限制最小生成树问题

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A novel genetic algorithm is proposed for degree-constrained Minimum Spanning Tree (short for d-MST) problem in this paper. First, a novel model that transfer d-MST problem into a preference two objective MST problem is presented. Based on this model, a new crossover operator, a local search scheme, a mutation operator and a new selection operator are designed based on the preference of the two objectives. Then, a new genetic algorithm (short for GA) is proposed. Furthermore, the convergence of the proposed algorithm to globally optimal solution with probability one is proved. The simulation results indicate the proposed algorithm is effective.
机译:本文提出了一种新的遗传算法,用于对学位受约束的最小生成树(短于D-MST)问题。首先,提出了一种新的模型,将D-MST问题转移到偏好中的偏好两个目标MST问题。基于该模型,基于两个目标的偏好,设计了一种新的交叉运算符,本地搜索方案,突变运算符和新选择运算符。然后,提出了一种新的遗传算法(GA的短路)。此外,证明了所提出的算法对全局最佳解决方案的概率算法。仿真结果表明所提出的算法是有效的。

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