搜索资源列表
SGA_for_testing
- 在软件测试的单元测试中,需要找出满足某种覆盖率(如分支覆盖)的测试数据(函数参数值)来判断被测函数是否有bug。源程序利用遗传算法的全局寻优特性实现了测试数据的自动产生而不用人工凭经验输入参数值。程序中被测试函数用的是三角函数。源码用C++实现了GA的寻优过程,并注有必要的注释,运行结果能够很快找到解。
GA
- 多目标的十进制遗传算法,可求解多个测试函数的多维的最优值-Multi-objective Genetic Algorithms decimal, multiple tests can be solved multidimensional optimal value function
GA_real_coded_min
- 采用遗传算法求最小值,比较实用,经过多个测试函数测试-Using genetic algorithms for the minimum
matlab--ga
- 采用遗传算法求最小值,比较实用,经过多个测试函数测试-Using genetic algorithms for the minimum
GA1
- 标准遗传算法,通过修改里面的测试函数即可为你所用!-Standard genetic algorithm, by modifying the inside of the test function can work for you!
Niche-genetic-algorithm
- 小生境遗传算法。模拟小生境在选择操作上进行改进,并在多个函数上进行测试分析。-Niche Genetic Algorithm. Analog niche in the choice of operating improvements, and test analysis on multiple functions.
examples
- 用于测试遗传算法算法效率的一系列算例,首先读入问题库和优化函数,然后利用算例的数据进行测试。-A series of examples for testing the efficiency of the algorithm genetic algorithm, first read the question bank and optimization functions, then use the data to test examples.
DeJong遗传算法
- 测试函数,matlab平台下的测试函数DeJong,对于用来遗传等智能算法的性能非常有用.(Test function, matlab platform under the test function DeJong, used for genetic and other intelligent algorithm performance is very useful.)
CEC 2017
- 测试函数:主要用于测试智能优化算法,如遗传算法、粒子群算法等的性能(Test function: it is mainly used to test the performance of intelligent optimization algorithms, such as genetic algorithm and particle swarm optimization algorithm)
带压缩,学习因子
- 在matlab用于各种算法粒子群和遗传的测试函数性能比较,画图等等(Performance comparison of particle swarm and genetic test functions used in various algorithms in matlab, drawing, etc.)