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Description: C++ implementation of a Genetic algorithm (GA). A population of binary chromosomes is generated randomly to attempt to solve the Weighted MAX SAT Problem. Parameters of crossover, mutation, population size can be controlled via macros in code.There are text files for testing on.
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Size: 15215616 |
Author: MJ |
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Description: 遗传算法 整个流程清晰明了 属于课程提交作业 有点精简-Clarity of the genetic algorithm process is a little program to streamline the job submission
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Size: 125952 |
Author: 斯科 |
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Description: GA比起SA ，最大的优势在于对个初始解，而且存在杂交和变异，让SA具有非常强的跳出局部最优解的能力。而且简单通用，健壮性强。但是待定的参数很多，而且计算速度比较慢。选择，杂交，变异算子的选取也很关键。-GA than SA, the biggest advantage of an initial solution, and there is hybridization and mutation, so that SA has a very strong ability to jump out of local optima. And simple generic, robust and strong. However, many parameters to be determined, and the calculation speed is slower. Selection, hybridization, mutation operator selection is also critical.
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Size: 89088 |
Author: JLH |
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Description: 采用遗传算法解决一个 MAX 3-SAT 问题，获得最优解。-to achieve best solution in solving MAX 3-SAT problem using genetic algorithm.
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Size: 17408 |
Author: 林曦 |
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