SAT Solver CNF Constraint Handling for Combinatorial Optimization

The patent segments the constraint handling into two distinct parts: (1) constraints transformed into CNF form are handled by the SAT solver, and (2) other constraints are handled by the simulated annealing process. This segmentation allows each solver to focus on its strengths, with the SAT solver efficiently handling logical constraints and the SA method optimizing the objective function, thereby reducing overall computation time while maintaining versatility.

The patent introduces an intermediary mechanism where constraints are transformed into CNF (Conjunctive Normal Form) and processed by a SAT solver before being fed into the simulated annealing process. This intermediary step acts as a bridge that pre-processes constraints in a form that accelerates the subsequent optimization, reducing the steepness issue and computation time while preserving the ability to handle diverse combinatorial optimization problems.

The patent segments the solution process into two phases: first, the SAT solver efficiently finds assignments that satisfy CNF-transformed constraints, and second, the simulated annealing process optimizes the objective function while respecting remaining constraints. This segmentation improves solution accuracy by ensuring constraints are systematically satisfied before optimization, reducing the steepness problem that plagues pure SA approaches.

The patent substitutes the purely mechanical simulated annealing constraint satisfaction mechanism with a logical SAT solving approach for CNF constraints. This substitution replaces the trial-and-error nature of SA constraint checking with a more rigorous logical deduction process, thereby improving solution accuracy and reliability while managing complexity through the use of established SAT solving algorithms.

The patent merges two established solving approaches—SAT solving and simulated annealing—into a hybrid system that leverages the strengths of both. By combining these solvers, the system achieves accelerated performance through the SAT solver's efficient constraint handling while maintaining the optimization capabilities of simulated annealing, thereby improving productivity without excessively increasing overall system complexity.

The patent creates a universal solver framework that can handle both CNF constraints (via SAT solver) and general optimization objectives (via simulated annealing) within a single integrated system. This multi-functional approach allows the same system architecture to process diverse constraint types and optimization problems, improving productivity across multiple problem domains while managing complexity through a unified interface.