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中文摘要：
提出一种将遗传算法与模拟退火算法相结合的SAT问题求解算法SAT-SAGA．该算法以遗传算法流程为主体，并把模拟退火机制融入其中，用以调整优化群体，防止陷入局部最优和出现早熟；在进化过程中算法采用了最优染色体保存策略，防止进化过程的发散．实验表明：该算法在求解速度、成功率和求解问题的规模等方面都有明显的改善．
英文摘要：
A novel algorithm, SAT-SAGA, is proposed for solving SAT problems based on the combination of the genetic algorithm and simulated annealing algorithm. The genetic algorithms are served as the main flow of the new algorithms which involve the mechanism of simulated annealing to adjust the optimization population, avoid trapping in local optimum and prevent precocity. The strategy of keeping the best chromosomes prevents the problem of convergence in the evolution iteration. The experimental results show that the SAT-SAGA performs remarkably better than a classical genetic algorithm in the aspects of speed, the success rate and the solvable problem scales.
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