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AAAI 2023

Improved Algorithms for Maximum Satisfiability and Its Special Cases

Conference Paper AAAI Technical Track on Constraint Satisfaction and Optimization Artificial Intelligence

Abstract

The Maximum Satisfiability (MAXSAT) problem is an optimization version of the Satisfiability problem (SAT) in which one is given a CNF formula with n variables and needs to find the maximum number of simultaneously satisfiable clauses. Recent works achieved significant progress in proving new upper bounds on the worst-case computational complexity of MAXSAT. All these works reduce general MAXSAT to a special case of MAXSAT where each variable appears a small number of times. So, it is important to design fast algorithms for (n,k)-MAXSAT to construct an efficient exact algorithm for MAXSAT. (n,k)-MAXSAT is a special case of MAXSAT where each variable appears at most k times in the input formula. For the (n,3)-MAXSAT problem, we design a O*(1.1749^n) algorithm improving on the previous record running time of O*(1.191^n). For the (n,4)-MAXSAT problem, we construct a O*(1.3803^n) algorithm improving on the previous best running time of O*(1.4254^n). Using the results, we develop a O*(1.0911^L) algorithm for the MAXSAT where L is a length of the input formula which improves previous algorithm with O*(1.0927^L) running time.

Authors

Keywords

  • CSO: Constraint Satisfaction
  • CSO: Satisfiability

Context

Venue
AAAI Conference on Artificial Intelligence
Archive span
1980-2026
Indexed papers
28718
Paper id
764712399153738852
v2026.09.13