Solving the maximum satisfiability problem by fuzzy converting it into a continuous optimization problem

L. Tseng, Chun Chen
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Abstract

The satisfiability problem is the first problem proved to be NP-Complete and has been one of the core NP-Complete problems since then. The satisfiability problem is a decision problem. And the maximum satisfiability problem is its optimization version that aims to find an assignment that satisfies most clauses. In this study, a fuzzy conversion method is proposed to convert the maximum satisfiability problem into a continuous optimization problem. Then the continuous optimization problem is solved by the multiple trajectory search that was previously proposed by us. The proposed fuzzy conversion method transforms the discrete search space into the continuous search space. Furthermore, the fitness function defined on this continuous search space is itself continuous. This fact makes the search much easier. An experiment was conducted to evaluate the performance of the proposed method. Comparison with several methods published in the literature reveals that the proposed method is promising.
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将最大可满足性问题模糊转化为连续优化问题,求解最大可满足性问题
可满足性问题是第一个被证明是np完全问题的问题,此后一直是np完全问题的核心之一。可满足性问题是一个决策问题。最大可满足性问题是它的优化版本,目的是找到一个满足大多数条件的分配。本文提出了一种模糊转换方法,将最大可满足性问题转化为连续优化问题。然后用我们之前提出的多轨迹搜索来解决连续优化问题。提出的模糊转换方法将离散搜索空间转化为连续搜索空间。并且,在这个连续搜索空间上定义的适应度函数本身是连续的。这个事实使得搜索更加容易。通过实验验证了该方法的性能。与文献中已发表的几种方法的比较表明,该方法是有前途的。
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