最大充足可能性問題に対するラグランジュの方法を用いた近似解法(一般講演)

抄録

The SAT (SATisfiability problem) is a problem to find a solution, namely, a 0,1 assignment to each variable which satisfies the given conjunctive normal form(CNF). The SAT is a fundamental and important NP complete problem in the field of information science. We proposed a neural network called LPPH for solving the SAT. The LPPH is known to be able to solve the SAT efficiently compared with conventional algorithms. The MAX SAT is a problem to find a solution which maximizes the summation of the importance of satisfied clauses, where the importance is given for each clause. In this paper, in order to solve MAX SAT, we propose coefficients which reflect the importance of clauses into the dynamics of the LPPH, and study the behavier of the dynamics experimentally.