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PARALLEL GENETIC ALGORITHM FOR SAT PROBLEMS BASED ON THE COARSE-GRAINED MODEL

机译:基于粗粒模型的SAT问题并行遗传算法

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The Genetic algorithm is a heuristic search algorithm. Using heuristic search algorithm for SAT problems is more effective than the traditional methods. However, simply use genetic algorithm for solving SAT problems can easily fall into local optimum. This paper presents a parallel genetic algorithm framework which based on coarse-grained model for solving SAT problems. The parallel mechanism can improve the solving speed and the coarse-grained model make it possible for that each compute node independently evolved, to ensure the diversity of the population.
机译:遗传算法是一种启发式搜索算法。使用SAT问题的启发式搜索算法比传统方法更有效。但是,只需使用用于解决SAT问题的遗传算法可以很容易地落入局部最佳状态。本文介绍了一种并行遗传算法框架,基于粗粒模型来解决SAT问题。并联机构可以提高求解速度,并且粗粒模型使得每个计算节点可以独立地演化,以确保群体的分集。

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