基于遗传算法的广义最小生成树求解与应用
The Solution and Application of the Generalized Minimum Spanning Tree Based on Genetic Algorithm
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摘要: 综合多目标最小生成树问题和度约束最小生成树问题, 对树每边赋予多重权条件, 加入节点度约束及约束的实现代价, 扩展了原广义最小生成树(GMST); 提出了根据种群成熟度自调整变异方式的变异算子以及限制父代个体保留数目的混合选择策略的遗传算法; 并用GMST和改进的遗传算法对网络进行建模和仿真, 验证了改进后的遗传算法有效可行, 且提高了解的质量; 最后利用该方法解决了农村有线电视网络经济布局的问题。Abstract: The limitation of traditional Minimum Spanning Tree problem was analyzed. The Multi-objective Minimum Spanning Tree problem and Degree-constrained Minimum Spanning Tree problem were integrated to put forward the new concept of Generalized Minimum Spanning Tree (GMST) based on the research of various constrained minimum tree problems and their solution algorithms. The edges of the minimum spanning tree are endowed with multi weights and the degree constraint and implement cost are introduced to meet the actual engineering needs. For the GMST is a combinatorial optimization problem which has multiple extremums, the simple Genetic Algorithm can not find optimal solution of high quality. So, a self-adjusting mutation operator based on maturity of the population and a hybrid selection strategy which can limit the parent individuals are designed. Finally, through the modeling and simulation of a cable television network, the applicability of GMST concept and effectivity of the improved genetic algorithm are proved. The economical arrangement for cable TV network is solved in rural areas.