sat

CP/SAT

This directory contains a next-gen Constraint Programming (CP) solver with clause learning. It is built on top of an efficient SAT/max-SAT solver whose code is also in this directory.

To begin, skim cp_model.proto to understand how optimization problems can be modeled using the solver. You can then solve a model with the functions in cp_model_solver.h.

Parameters

• sat_parameters.proto: The SAT solver parameters. Also contains max-SAT and CP parameters.

Model

The optimization model description and related utilities:

• cp_model.proto: Proto describing a general Constraint Programming model.
• cp_model_utils.h: Utilities to manipulate and create a cp_model.proto.
• cp_model_checker.h: Tools to validate cp_model.proto and test a solution feasibility.
• cp_model_solver.h: The solver API.
• cp_model_presolve.h: Presolve a cp_model.proto by applying simple rules to simplify a subsequent solve.

SAT solver

Stand-alone SAT solver and related files. Note that this is more than a basic SAT solver as it already includes non-clause constraints. However, these do not work on the general integer problems that the CP solver handles.

Pure SAT solver:

• sat_base.h: SAT core classes.
• clause.h: SAT clause propagator with the two-watcher mechanism. Also contains propagators for binary clauses.
• sat_solver.h: The SatSolver code.
• simplification.h: SAT postsolver and presolver.
• symmetry.h: Dynamic symmetry breaking constraint in SAT. Not used by default.

Extension:

• pb_constraint.h: Implementation of a Pseudo-Boolean constraint propagator for SAT. Pseudo-Boolean constraints are simply another name used in the SAT community for linear constraints on Booleans.
• no_cycle.h: Implementation of a no-cycle constraint on a graph whose arc presences are controlled by Boolean. This is a SAT propagator, not used in CP.
• encoding.h: Basic algorithm to encode integer variables into a binary representation. This is not used by the CP solver, just by the max-SAT core based algorithm in optimization.h.

Input/output:

• drat_writer.h: Write UNSAT proof in the DRAT format. This allows to check the correctness of an UNSAT proof with the third party program DRAT-trim.
• opb_reader.h: Parser for the .opb format for Pseudo-Boolean optimization problems.
• sat_cnf_reader.h: Parser for the classic SAT .cnf format. Also parses max-SAT files.
• boolean_problem.proto: Deprecated by cp_model.proto.

CP solver

CP solver built on top of the SAT solver:

• integer.h: The entry point, which defines the core of the solver.

Basic constraints:

• all_different.h: Propagation algorithms for the AllDifferent constraint.
• integer_expr.h: Propagation algorithms for integer expression (linear, max, min, div, mod, ...).
• table.h: Propagation algorithms for the table and automaton constraints.
• precedences.h: Propagation algorithms for integer inequalities (integer difference logic theory).
• cp_constraints.h: Propagation algorithms for other classic CP constraints (XOR, circuit, non-overlapping rectangles, ...)
• linear_programming_constraint.h: Constraint that solves an LP relaxation of a set of constraints and uses the dual-ray to explain an eventual infeasibility. Also implements reduced-cost fixing.
• flow_costs.h: Deprecated. Network flow constraint. We use the generic linear_programming_constraint instead.

Scheduling constraints:

• intervals.h: Definition and utility for manipulating "interval" variables (a.k.a. task or activities). This is the basic CP variable type used in scheduling problems.
• disjunctive.h: Propagation algorithms for the disjunctive scheduling constraint.
• cumulative.h, timetable.h, overload_checker.h, timetable_edgefinding.h: Propagation algorithms for the cumulative scheduling constraint.
• cumulative_energy.h: Propagation algorithms for a more general cumulative constraint.
• theta_tree.h: Data structure used in the cumulative/disjunctive propagation algorithm.

Other

• model.h: Generic class that implements a basic dependency injection framework for singleton objects and manages the memory ownership of all the solver classes.
• optimization.h: Algorithms to solve an optimization problem using a satisfiability solver as a black box.
• lp_utils.h: Utility to scale and convert a MIP model into CP.

Recipes

You can find a set a code recipes in the documentation directory.