Search - crossover in Genetic algorithm in TSP

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[Other] mgasa DL : 0: 本资源是Mgasa算法解决TSP问题的Matlab代码，资源中包括mgasa_main(Mgasa算法解决TSP问题代码)，mgasa_fitness(适应度求取函数代码)，mgasa_annealing(Mgasa算法中模拟退火代码)，mgasa_select(遗传算法中选择函数代码)，mgasa_crossover(遗传算法中染色体交叉互换函数代码)，mgasa_mutation(遗传算法中基因突变函数代码)，mgasa_change(Mgasa算法中选择过程代码)。同时代码中有Location矩阵，其中30个坐标作为TSP问题的例子。-This resource is Mgasa algorithm to solve the TSP problem matlab code, resources including the mgasa_main, the algorithm Mgasa solutions TSP code, mgasa_fitness (adaptation degree to obtain the function code), mgasa_annealing (Mgasa algorithm simulated annealing of code), mgasa_ (genetic algorithm selection function code), mgasa_crossover (genetic algorithm crossover swap function code), mgasa_mutation(genetic algorithm in gene mutation function code), mgasa_change(algorithm Mgasa selects the process of code). At the same time the code in the Location matrix, where 30 coordinates as an example of the TSP problem.
Date : 2025-12-28 Size : 4kb User : lfr
[Other] TSP-PSO DL : 0: 混合粒子群算法摒弃了传统粒子群算法中的通过跟踪极值来更新粒子位置的方法，而是引入了遗传算法中的交叉和变异操作，通过粒子同个体极值和群体极值的交叉以及粒子自身变异的方式来搜索最优解。(Hybrid particle swarm algorithm instead of the traditional particle swarm algorithm in the method to update the position of the particle by tracking the maximum, but the introduction of crossover and mutation in genetic algorithm, the particle swarm extremum with individual extremum and cross and variation of the particle itself to search the optimal solution.)
Date : 2025-12-28 Size : 13kb User : 胡萝卜须