Research on the Application of Election Algorithms in the GRAN3SAT

Satisfiability (SAT) rules are a well-known combinatorial optimization challenge with numerous applications in computer science and engineering. This paper proposes an evolutionary algorithm-based election strategy to enhance the solving of higher-order logical rules. The approach aims to balance complexity and efficiency, improving the quality and speed of problem-solving while offering more reliable and practical solutions. By integrating the Election Algorithm (EA) with the logical rules of GRAN3SAT, the study generates 100 random combinations to evaluate performance. The effectiveness of the EA is assessed based on three key metrics: average iteration count, time complexity, and fitness function. Experimental results indicate that the EA achieves high reliability and low computational cost within limited iterations. Compared to the Exhaustive Search Algorithm (ES), the EA demonstrates superior reliability, stability, and practicality in addressing higher-order logical rules.