operations_research::sat::LocalBranchingLpBasedNeighborhoodGenerator Class Reference

#include <cp_model_lns.h>

Inheritance diagram for operations_research::sat::LocalBranchingLpBasedNeighborhoodGenerator:

Public Member Functions
	LocalBranchingLpBasedNeighborhoodGenerator (NeighborhoodGeneratorHelper const *helper, absl::string_view name, std::function< void(CpModelProto, Model *)> solve_callback, ModelSharedTimeLimit *const global_time_limit)
Neighborhood	Generate (const CpSolverResponse &initial_solution, double difficulty, absl::BitGenRef random) final
Public Member Functions inherited from operations_research::sat::NeighborhoodGenerator
	NeighborhoodGenerator (absl::string_view name, NeighborhoodGeneratorHelper const *helper)
virtual	~NeighborhoodGenerator ()=default
virtual bool	ReadyToGenerate () const
	Returns true if the neighborhood generator can generate a neighborhood.
double	GetUCBScore (int64_t total_num_calls) const
void	AddSolveData (SolveData data)
double	Synchronize ()
std::string	name () const
	Returns a short description of the generator.
int64_t	num_calls () const
	Number of times this generator was called.
int64_t	num_fully_solved_calls () const
	Number of time the neighborhood was fully solved (OPTIMAL/INFEASIBLE).
int64_t	num_improving_calls () const
	Out of num_calls(), how many improved the given solution.
int64_t	num_consecutive_non_improving_calls () const
double	difficulty () const
	The current difficulty of this generator.
double	deterministic_limit () const
	The current time limit that the sub-solve should use on this generator.

Additional Inherited Members
Protected Attributes inherited from operations_research::sat::NeighborhoodGenerator
const std::string	name_
const NeighborhoodGeneratorHelper &	helper_
absl::Mutex	generator_mutex_

Detailed Description

Solves a local branching LP and greedily picks a set of variables with the largest differences between the initial and local branching LP solutions, breaking ties uniformly at random.

This is based on Huang et al., "Local Branching Relaxation Heuristics for Integer Linear Programs", 2023.

Definition at line 594 of file cp_model_lns.h.

Constructor & Destructor Documentation

LocalBranchingLpBasedNeighborhoodGenerator()

operations_research::sat::LocalBranchingLpBasedNeighborhoodGenerator::LocalBranchingLpBasedNeighborhoodGenerator ( NeighborhoodGeneratorHelper const * helper, absl::string_view name, std::function< void(CpModelProto, Model *)> solve_callback, ModelSharedTimeLimit *const global_time_limit )

inlineexplicit

Todo

(user): Restructure code so that we avoid circular dependency with solving functions. For now, we use solve_callback.

Definition at line 599 of file cp_model_lns.h.

Member Function Documentation

Generate()

Neighborhood operations_research::sat::LocalBranchingLpBasedNeighborhoodGenerator::Generate ( const CpSolverResponse & initial_solution, double difficulty, absl::BitGenRef random )

finalvirtual

Generates a "local" subproblem for the given seed.

The difficulty will be in [0, 1] and is related to the asked neighborhood size (and thus local problem difficulty). A difficulty of 0.0 means empty neighborhood and a difficulty of 1.0 means the full problem. The algorithm should try to generate a neighborhood according to this difficulty which will be dynamically adjusted depending on whether or not we can solve the subproblem in a given time limit.

The given initial_solution should contain a feasible solution to the initial CpModelProto given to this class. Any solution to the returned CPModelProto should also be valid solution to the same initial model.

This function should be thread-safe.

Collect active binary variables and corresponding initial solution values.

Todo

(user): Extend to integer variables.

Create and solve local branching LP.

Parameters to enable solving the LP only.

Parameters to attempt to speed up solve.

Parameters to limit time spent in the solve. The max number of iterations is relaxed from the default since we rely more on deterministic time.

Skip LNS if no (full) feasible solution was found for the LP.

Compute differences between LP solution and initial solution, with a small random noise for tie breaking.

Take the target_size variables with largest differences.

For now, we include all non-binary variables in the relaxation, since their values are likely tied to the binary values.

Implements operations_research::sat::NeighborhoodGenerator.

Definition at line 1756 of file cp_model_lns.cc.

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The documentation for this class was generated from the following files:

• ortools/sat/cp_model_lns.h
• ortools/sat/cp_model_lns.cc