Method for solving Boolean satisfiability problem based on extension rule

Abstract

The invention discloses a method for solving a Boolean satisfiability problem based on an extension rule, and the method comprises the steps: firstly designing a CCAER heuristic expression and PAWSERplanning suitable for the extension rule, and inventing a Subscoerer attribute and a CScoreer attribute of variables, wherein the CCAER heuristic expression is a certain overturning opportunity givento variables which exceed a certain threshold but have no change in pattern, and the PAWSER planning is mainly used for updating clause weights. For an example in a phase change interval, the CScoreerattribute of the variables is adopted; for an example which is not in a phase change interval, the Subscoerer attribute of a variable is adopted. Then, during initialization, an IMOM thought is utilized to obtain an initial maximum item, so that an initial solution is closer to an actual solution space, and the number of overturning times is reduced; and finally, the satisfiability of the subspace is judged in the searching process, if the satisfiability is met, a solution is found, and otherwise, we continue to judge the satisfiability of the whole space.

Description

technical field [0001] The invention relates to the technical field of solving Boolean satisfiability problems, in particular to a method for solving Boolean satisfiability problems based on extended rules. Background technique [0002] Boolean Satisfiability Problem (SAT problem for short) is a well-known decision problem, which not only has a pivotal research position in mathematical logic and computational theory, but also has high application value in the field of actual production. The SAT problem is a basic problem in logic, and it is also the core problem in computer science and artificial intelligence research today. Many important issues in engineering technology, military affairs, business administration, transportation and natural science research, such as automatic switching of program-controlled telephones, maintenance of large databases, automatic wiring of large-scale integrated circuits, automatic software development, robot action planning, etc. Can be conv...

AI Technical Summary

Problems solved by technology

However, when the ERACC algorithm avoids falling into local optimum, it uses CC ER Inspired Strategies, the CC ER The principle of inspiration is that if a variable has not changed its pattern since the last flip, flipping is prohibited, even if its flipping can bring many benefits, which affects the solution efficiency of the ERACC algorithm to a certain extent