MPSolver (com.google.ortools:ortools-java 9.10.4067 API)

java.lang.Object
- com.google.ortools.linearsolver.MPSolver

```
public class MPSolver
extends java.lang.Object
```
This mathematical programming (MP) solver class is the main class
though which users build and solve problems.

Nested Class Summary

Nested Classes
Modifier and Type	Class and Description
`static class`	`MPSolver.BasisStatus` Advanced usage: possible basis status values for a variable and the slack variable of a linear constraint.
`static class`	`MPSolver.OptimizationProblemType` The type of problems (LP or MIP) that will be solved and the underlying solver (GLOP, GLPK, CLP, CBC or SCIP) that will solve them.
`static class`	`MPSolver.ResultStatus` The status of solving the problem.

Field Summary

Fields
Modifier and Type Field and Description

protected boolean swigCMemOwn

Fields
Modifier and Type	Field and Description
`protected boolean`	`swigCMemOwn`

Constructor Summary

Constructors
Modifier	Constructor and Description
`protected`	`MPSolver(long cPtr, boolean cMemoryOwn)`
	`MPSolver(java.lang.String name, MPSolver.OptimizationProblemType problem_type)` Create a solver with the given name and underlying solver backend.

Method Summary

All Methods Static Methods Instance Methods Concrete Methods
Modifier and Type	Method and Description
`void`	`clear()` Clears the objective (including the optimization direction), all variables and constraints.
`double[]`	`computeConstraintActivities()` Advanced usage: compute the "activities" of all constraints, which are the sums of their linear terms.
`double`	`computeExactConditionNumber()` Advanced usage: computes the exact condition number of the current scaled basis: L1norm(B) * L1norm(inverse(B)), where B is the scaled basis. This method requires that a basis exists: it should be called after Solve. It is only available for continuous problems.
`MPConstraint`	`constraint(int index)` Returns the constraint at the given index.
`MPConstraint[]`	`constraints()` Returns the array of constraints handled by the MPSolver. They are listed in the order in which they were created.
`MPSolutionResponse`	`createSolutionResponseProto()` Fills the solution found to a response proto and returns it.
`static MPSolver`	`createSolver(java.lang.String solver_id)` Recommended factory method to create a MPSolver instance, especially in non C++ languages. It returns a newly created solver instance if successful, or a nullptr otherwise.
`void`	`delete()`
`void`	`enableOutput()` Enables solver logging.
`java.lang.String`	`exportModelAsLpFormat()` Export the loaded model in LP format.
`java.lang.String`	`exportModelAsLpFormat(MPModelExportOptions options)` Export the loaded model in LP format.
`java.lang.String`	`exportModelAsMpsFormat()` Export the loaded model in MPS format.
`java.lang.String`	`exportModelAsMpsFormat(MPModelExportOptions options)` Export the loaded model in MPS format.
`MPModelProto`	`exportModelToProto()` Export the loaded model to proto and returns it.
`protected void`	`finalize()`
`protected static long`	`getCPtr(MPSolver obj)`
`static double`	`infinity()` Infinity. You can use -MPSolver::infinity() for negative infinity.
`boolean`	`interruptSolve()` Interrupts the Solve() execution to terminate processing if possible. If the underlying interface supports interruption; it does that and returns true regardless of whether there's an ongoing Solve() or not.
`boolean`	`isMip()`
`long`	`iterations()` Returns the number of simplex iterations.
`java.lang.String`	`loadModelFromProto(MPModelProto input_model)` Loads a model and returns the error message, which will be empty iff the model is valid.
`java.lang.String`	`loadModelFromProtoKeepNames(MPModelProto input_model)` Like loadModelFromProto(), but keeps the names and returns an error if there are duplicate names.
`java.lang.String`	`loadModelFromProtoWithUniqueNamesOrDie(MPModelProto input_model)`
`boolean`	`loadSolutionFromProto(MPSolutionResponse response)` Load a solution encoded in a protocol buffer onto this solver for easy access via the MPSolver interface. IMPORTANT: This may only be used in conjunction with ExportModel(), following this example: {@code MPSolver my_solver; ...
`MPConstraint`	`lookupConstraintOrNull(java.lang.String constraint_name)` Looks up a constraint by name, and returns nullptr if it does not exist. The first call has a O(n) complexity, as the constraint name index is lazily created upon first use.
`MPVariable`	`lookupVariableOrNull(java.lang.String var_name)` Looks up a variable by name, and returns nullptr if it does not exist.
`MPVariable`	`makeBoolVar(java.lang.String name)` Creates a boolean variable.
`MPVariable[]`	`makeBoolVarArray(int count)`
`MPVariable[]`	`makeBoolVarArray(int count, java.lang.String var_name)`
`MPConstraint`	`makeConstraint()` Creates a constraint with -infinity and +infinity bounds.
`MPConstraint`	`makeConstraint(double lb, double ub)` Creates a linear constraint with given bounds. Bounds can be finite or +/- MPSolver::infinity().
`MPConstraint`	`makeConstraint(double lb, double ub, java.lang.String name)` Creates a named constraint with given bounds.
`MPConstraint`	`makeConstraint(java.lang.String name)` Creates a named constraint with -infinity and +infinity bounds.
`MPVariable`	`makeIntVar(double lb, double ub, java.lang.String name)` Creates an integer variable.
`MPVariable[]`	`makeIntVarArray(int count, double lb, double ub)`
`MPVariable[]`	`makeIntVarArray(int count, double lb, double ub, java.lang.String var_name)`
`MPVariable`	`makeNumVar(double lb, double ub, java.lang.String name)` Creates a continuous variable.
`MPVariable[]`	`makeNumVarArray(int count, double lb, double ub)`
`MPVariable[]`	`makeNumVarArray(int count, double lb, double ub, java.lang.String var_name)`
`MPVariable`	`makeVar(double lb, double ub, boolean integer, java.lang.String name)` Creates a variable with the given bounds, integrality requirement and name.
`MPVariable[]`	`makeVarArray(int count, double lb, double ub, boolean integer)` Creates and returns an array of variables.
`MPVariable[]`	`makeVarArray(int count, double lb, double ub, boolean integer, java.lang.String var_name)` Creates and returns an array of named variables.
`long`	`nodes()` Returns the number of branch-and-bound nodes evaluated during the solve. Only available for discrete problems.
`int`	`numConstraints()` Returns the number of constraints.
`int`	`numVariables()` Returns the number of variables.
`MPObjective`	`objective()` Returns the mutable objective object.
`MPSolver.OptimizationProblemType`	`problemType()` Returns the optimization problem type set at construction.
`void`	`reset()` Advanced usage: resets extracted model to solve from scratch. This won't reset the parameters that were set with SetSolverSpecificParametersAsString() or set_time_limit() or even clear the linear program.
`void`	`setHint(MPVariable[] variables, double[] values)` Sets a hint for solution. If a feasible or almost-feasible solution to the problem is already known, it may be helpful to pass it to the solver so that it can be used.
`boolean`	`setNumThreads(int num_theads)` Sets the number of threads to be used by the solver.
`boolean`	`setSolverSpecificParametersAsString(java.lang.String parameters)` Advanced usage: pass solver specific parameters in text format. The format is solver-specific and is the same as the corresponding solver configuration file format.
`void`	`setTimeLimit(long time_limit_milliseconds)`
`MPSolver.ResultStatus`	`solve()` Solves the problem using the default parameter values.
`MPSolver.ResultStatus`	`solve(MPSolverParameters param)` Solves the problem using the specified parameter values.
`java.lang.String`	`solverVersion()` Returns a string describing the underlying solver and its version.
`static MPSolutionResponse`	`solveWithProto(MPModelRequest model_request)` Solves the given model proto and returns a response proto.
`static boolean`	`supportsProblemType(MPSolver.OptimizationProblemType problem_type)` Whether the given problem type is supported (this will depend on the targets that you linked).
`void`	`suppressOutput()` Suppresses solver logging.
`protected static long`	`swigRelease(MPSolver obj)`
`MPVariable`	`variable(int index)` Returns the variable at position index.
`MPVariable[]`	`variables()` Returns the array of variables handled by the MPSolver.
`boolean`	`verifySolution(double tolerance, boolean log_errors)` Advanced usage: Verifies the correctness of the solution. It verifies that all variables must be within their domains, all constraints must be satisfied, and the reported objective value must be accurate. Usage: - This can only be called after Solve() was called. - "tolerance" is interpreted as an absolute error threshold. - For the objective value only, if the absolute error is too large, the tolerance is interpreted as a relative error threshold instead. - If "log_errors" is true, every single violation will be logged. - If "tolerance" is negative, it will be set to infinity(). Most users should just set the --verify_solution flag and not bother using this method directly.
`long`	`wallTime()`
`void`	`write(java.lang.String file_name)` Writes the model using the solver internal write function.

Methods inherited from class java.lang.Object
clone, equals, getClass, hashCode, notify, notifyAll, toString, wait, wait, wait

- Field Detail
  - swigCMemOwn
```
protected transient boolean swigCMemOwn
```
- Constructor Detail
  - MPSolver
```
protected MPSolver(long cPtr,
                   boolean cMemoryOwn)
```
  - MPSolver
```
public MPSolver(java.lang.String name,
                MPSolver.OptimizationProblemType problem_type)
```
    Create a solver with the given name and underlying solver backend.
- Method Detail
  - getCPtr
```
protected static long getCPtr(MPSolver obj)
```
  - swigRelease
```
protected static long swigRelease(MPSolver obj)
```
  - finalize
```
protected void finalize()
```
    Overrides:
    
    finalize in class java.lang.Object
  - delete
```
public void delete()
```
  - makeVarArray
```
public MPVariable[] makeVarArray(int count,
                                 double lb,
                                 double ub,
                                 boolean integer)
```
    Creates and returns an array of variables.
  - makeVarArray
```
public MPVariable[] makeVarArray(int count,
                                 double lb,
                                 double ub,
                                 boolean integer,
                                 java.lang.String var_name)
```
    Creates and returns an array of named variables.
  - makeNumVarArray
```
public MPVariable[] makeNumVarArray(int count,
                                    double lb,
                                    double ub)
```
  - makeNumVarArray
```
public MPVariable[] makeNumVarArray(int count,
                                    double lb,
                                    double ub,
                                    java.lang.String var_name)
```
  - makeIntVarArray
```
public MPVariable[] makeIntVarArray(int count,
                                    double lb,
                                    double ub)
```
  - makeIntVarArray
```
public MPVariable[] makeIntVarArray(int count,
                                    double lb,
                                    double ub,
                                    java.lang.String var_name)
```
  - makeBoolVarArray
```
public MPVariable[] makeBoolVarArray(int count)
```
  - makeBoolVarArray
```
public MPVariable[] makeBoolVarArray(int count,
                                     java.lang.String var_name)
```
  - createSolver
```
public static MPSolver createSolver(java.lang.String solver_id)
```
    Recommended factory method to create a MPSolver instance, especially in
    non C++ languages.
    
    It returns a newly created solver instance if successful, or a nullptr
    otherwise. This can occur if the relevant interface is not linked in, or if
    a needed license is not accessible for commercial solvers.
    
    Ownership of the solver is passed on to the caller of this method.
    It will accept both string names of the OptimizationProblemType enum, as
    well as a short version (i.e. "SCIP_MIXED_INTEGER_PROGRAMMING" or "SCIP").
    
    solver_id is case insensitive, and the following names are supported:
    - CLP_LINEAR_PROGRAMMING or CLP
    - CBC_MIXED_INTEGER_PROGRAMMING or CBC
    - GLOP_LINEAR_PROGRAMMING or GLOP
    - BOP_INTEGER_PROGRAMMING or BOP
    - SAT_INTEGER_PROGRAMMING or SAT or CP_SAT
    - SCIP_MIXED_INTEGER_PROGRAMMING or SCIP
    - GUROBI_LINEAR_PROGRAMMING or GUROBI_LP
    - GUROBI_MIXED_INTEGER_PROGRAMMING or GUROBI or GUROBI_MIP
    - CPLEX_LINEAR_PROGRAMMING or CPLEX_LP
    - CPLEX_MIXED_INTEGER_PROGRAMMING or CPLEX or CPLEX_MIP
    - XPRESS_LINEAR_PROGRAMMING or XPRESS_LP
    - XPRESS_MIXED_INTEGER_PROGRAMMING or XPRESS or XPRESS_MIP
    - GLPK_LINEAR_PROGRAMMING or GLPK_LP
    - GLPK_MIXED_INTEGER_PROGRAMMING or GLPK or GLPK_MIP
  - supportsProblemType
```
public static boolean supportsProblemType(MPSolver.OptimizationProblemType problem_type)
```
    Whether the given problem type is supported (this will depend on the
    targets that you linked).
  - isMip
```
public boolean isMip()
```
  - problemType
```
public MPSolver.OptimizationProblemType problemType()
```
    Returns the optimization problem type set at construction.
  - clear
```
public void clear()
```
    Clears the objective (including the optimization direction), all variables
    and constraints. All the other properties of the MPSolver (like the time
    limit) are kept untouched.
  - numVariables
```
public int numVariables()
```
    Returns the number of variables.
  - variables
```
public MPVariable[] variables()
```
    Returns the array of variables handled by the MPSolver. (They are listed in
    the order in which they were created.)
  - variable
```
public MPVariable variable(int index)
```
    Returns the variable at position index.
  - lookupVariableOrNull
```
public MPVariable lookupVariableOrNull(java.lang.String var_name)
```
    Looks up a variable by name, and returns nullptr if it does not exist. The
    first call has a O(n) complexity, as the variable name index is lazily
    created upon first use. Will crash if variable names are not unique.
  - makeVar
```
public MPVariable makeVar(double lb,
                          double ub,
                          boolean integer,
                          java.lang.String name)
```
    Creates a variable with the given bounds, integrality requirement and
    name. Bounds can be finite or +/- MPSolver::infinity(). The MPSolver owns
    the variable (i.e. the returned pointer is borrowed). Variable names are
    optional. If you give an empty name, name() will auto-generate one for you
    upon request.
  - makeNumVar
```
public MPVariable makeNumVar(double lb,
                             double ub,
                             java.lang.String name)
```
    Creates a continuous variable.
  - makeIntVar
```
public MPVariable makeIntVar(double lb,
                             double ub,
                             java.lang.String name)
```
    Creates an integer variable.
  - makeBoolVar
```
public MPVariable makeBoolVar(java.lang.String name)
```
    Creates a boolean variable.
  - numConstraints
```
public int numConstraints()
```
    Returns the number of constraints.
  - constraints
```
public MPConstraint[] constraints()
```
    Returns the array of constraints handled by the MPSolver.
    
    They are listed in the order in which they were created.
  - constraint
```
public MPConstraint constraint(int index)
```
    Returns the constraint at the given index.
  - lookupConstraintOrNull
```
public MPConstraint lookupConstraintOrNull(java.lang.String constraint_name)
```
    Looks up a constraint by name, and returns nullptr if it does not exist.
    
    The first call has a O(n) complexity, as the constraint name index is
    lazily created upon first use. Will crash if constraint names are not
    unique.
  - makeConstraint
```
public MPConstraint makeConstraint(double lb,
                                   double ub)
```
    Creates a linear constraint with given bounds.
    
    Bounds can be finite or +/- MPSolver::infinity(). The MPSolver class
    assumes ownership of the constraint.
    
    Returns:
    
    a pointer to the newly created constraint.
  - makeConstraint
```
public MPConstraint makeConstraint()
```
    Creates a constraint with -infinity and +infinity bounds.
  - makeConstraint
```
public MPConstraint makeConstraint(double lb,
                                   double ub,
                                   java.lang.String name)
```
    Creates a named constraint with given bounds.
  - makeConstraint
```
public MPConstraint makeConstraint(java.lang.String name)
```
    Creates a named constraint with -infinity and +infinity bounds.
  - objective
```
public MPObjective objective()
```
    Returns the mutable objective object.
  - solve
```
public MPSolver.ResultStatus solve()
```
    Solves the problem using the default parameter values.
  - solve
```
public MPSolver.ResultStatus solve(MPSolverParameters param)
```
    Solves the problem using the specified parameter values.
  - write
```
public void write(java.lang.String file_name)
```
    Writes the model using the solver internal write function. Currently only
    available for Gurobi.
  - computeConstraintActivities
```
public double[] computeConstraintActivities()
```
    Advanced usage: compute the "activities" of all constraints, which are the
    sums of their linear terms. The activities are returned in the same order
    as constraints(), which is the order in which constraints were added; but
    you can also use MPConstraint::index() to get a constraint's index.
  - verifySolution
```
public boolean verifySolution(double tolerance,
                              boolean log_errors)
```
    Advanced usage: Verifies the *correctness* of the solution.
    
    It verifies that all variables must be within their domains, all
    constraints must be satisfied, and the reported objective value must be
    accurate.
    
    Usage:
    - This can only be called after Solve() was called.
    - "tolerance" is interpreted as an absolute error threshold.
    - For the objective value only, if the absolute error is too large,
    the tolerance is interpreted as a relative error threshold instead.
    - If "log_errors" is true, every single violation will be logged.
    - If "tolerance" is negative, it will be set to infinity().
    
    Most users should just set the --verify_solution flag and not bother using
    this method directly.
  - reset
```
public void reset()
```
    Advanced usage: resets extracted model to solve from scratch.
    
    This won't reset the parameters that were set with
    SetSolverSpecificParametersAsString() or set_time_limit() or even clear the
    linear program. It will just make sure that next Solve() will be as if
    everything was reconstructed from scratch.
  - interruptSolve
```
public boolean interruptSolve()
```
    Interrupts the Solve() execution to terminate processing if possible.
    
    If the underlying interface supports interruption; it does that and returns
    true regardless of whether there's an ongoing Solve() or not. The Solve()
    call may still linger for a while depending on the conditions. If
    interruption is not supported; returns false and does nothing.
    MPSolver::SolverTypeSupportsInterruption can be used to check if
    interruption is supported for a given solver type.
  - setSolverSpecificParametersAsString
```
public boolean setSolverSpecificParametersAsString(java.lang.String parameters)
```
    Advanced usage: pass solver specific parameters in text format.
    
    The format is solver-specific and is the same as the corresponding solver
    configuration file format. Returns true if the operation was successful.
  - infinity
```
public static double infinity()
```
    Infinity.
    
    You can use -MPSolver::infinity() for negative infinity.
  - enableOutput
```
public void enableOutput()
```
    Enables solver logging.
  - suppressOutput
```
public void suppressOutput()
```
    Suppresses solver logging.
  - iterations
```
public long iterations()
```
    Returns the number of simplex iterations.
  - nodes
```
public long nodes()
```
    Returns the number of branch-and-bound nodes evaluated during the solve.
    
    Only available for discrete problems.
  - solverVersion
```
public java.lang.String solverVersion()
```
    Returns a string describing the underlying solver and its version.
  - computeExactConditionNumber
```
public double computeExactConditionNumber()
```
    Advanced usage: computes the exact condition number of the current scaled
    basis: L1norm(B) * L1norm(inverse(B)), where B is the scaled basis.
    
    This method requires that a basis exists: it should be called after Solve.
    It is only available for continuous problems. It is implemented for GLPK
    but not CLP because CLP does not provide the API for doing it.
    
    The condition number measures how well the constraint matrix is conditioned
    and can be used to predict whether numerical issues will arise during the
    solve: the model is declared infeasible whereas it is feasible (or
    vice-versa), the solution obtained is not optimal or violates some
    constraints, the resolution is slow because of repeated singularities.
    
    The rule of thumb to interpret the condition number kappa is:
    - o kappa <= 1e7: virtually no chance of numerical issues
    - o 1e7 < kappa <= 1e10: small chance of numerical issues
    - o 1e10 < kappa <= 1e13: medium chance of numerical issues
    - o kappa > 1e13: high chance of numerical issues
    
    The computation of the condition number depends on the quality of the LU
    decomposition, so it is not very accurate when the matrix is ill
    conditioned.
  - setTimeLimit
```
public void setTimeLimit(long time_limit_milliseconds)
```
  - wallTime
```
public long wallTime()
```
  - loadModelFromProto
```
public java.lang.String loadModelFromProto(MPModelProto input_model)
```
    Loads a model and returns the error message, which will be empty iff the
    model is valid. Clears all names (see also loadModelFromProtoKeepNames()).
  - loadModelFromProtoKeepNames
```
public java.lang.String loadModelFromProtoKeepNames(MPModelProto input_model)
```
    Like loadModelFromProto(), but keeps the names and returns an error if
    there are duplicate names.
  - loadModelFromProtoWithUniqueNamesOrDie
```
public java.lang.String loadModelFromProtoWithUniqueNamesOrDie(MPModelProto input_model)
```
  - exportModelToProto
```
public MPModelProto exportModelToProto()
```
    Export the loaded model to proto and returns it.
  - createSolutionResponseProto
```
public MPSolutionResponse createSolutionResponseProto()
```
    Fills the solution found to a response proto and returns it.
  - loadSolutionFromProto
```
public boolean loadSolutionFromProto(MPSolutionResponse response)
```
    Load a solution encoded in a protocol buffer onto this solver for easy
    access via the MPSolver interface.
    
    IMPORTANT: This may only be used in conjunction with ExportModel(),
    following this example:
    
    MPSolver my_solver; ... add variables and constraints ... MPModelProto model_proto; my_solver.ExportModelToProto(&model_proto); MPSolutionResponse solver_response; MPSolver::SolveWithProto(model_proto, &solver_response); if (solver_response.result_status() == MPSolutionResponse::OPTIMAL) { CHECK_OK(my_solver.LoadSolutionFromProto(solver_response)); ... inspect the solution using the usual API: solution_value(), etc... }
    
    The response must be in OPTIMAL or FEASIBLE status.
    
    Returns a false if a problem arised (typically, if it wasn't used
    like it should be):
    - loading a solution whose variables don't correspond to the solver's
    current variables
    - loading a solution with a status other than OPTIMAL / FEASIBLE.
    
    Note: the objective value isn't checked. You can use VerifySolution() for
    that.
  - solveWithProto
```
public static MPSolutionResponse solveWithProto(MPModelRequest model_request)
```
    Solves the given model proto and returns a response proto.
  - exportModelAsLpFormat
```
public java.lang.String exportModelAsLpFormat(MPModelExportOptions options)
```
    Export the loaded model in LP format.
  - exportModelAsLpFormat
```
public java.lang.String exportModelAsLpFormat()
```
    Export the loaded model in LP format.
  - exportModelAsMpsFormat
```
public java.lang.String exportModelAsMpsFormat(MPModelExportOptions options)
```
    Export the loaded model in MPS format.
  - exportModelAsMpsFormat
```
public java.lang.String exportModelAsMpsFormat()
```
    Export the loaded model in MPS format.
  - setHint
```
public void setHint(MPVariable[] variables,
                    double[] values)
```
    Sets a hint for solution.
    
    If a feasible or almost-feasible solution to the problem is already known,
    it may be helpful to pass it to the solver so that it can be used. A
    solver that supports this feature will try to use this information to
    create its initial feasible solution.
    
    Note that it may not always be faster to give a hint like this to the
    solver. There is also no guarantee that the solver will use this hint or
    try to return a solution "close" to this assignment in case of multiple
    optimal solutions.
  - setNumThreads
```
public boolean setNumThreads(int num_theads)
```
    Sets the number of threads to be used by the solver.

Class MPSolver

Nested Class Summary

Field Summary

Constructor Summary

Method Summary

Methods inherited from class java.lang.Object

Field Detail

swigCMemOwn

Constructor Detail

MPSolver

MPSolver

Method Detail

getCPtr

swigRelease

finalize

delete

makeVarArray

makeVarArray

makeNumVarArray

makeNumVarArray

makeIntVarArray

makeIntVarArray

makeBoolVarArray

makeBoolVarArray

createSolver

supportsProblemType

isMip

problemType

clear

numVariables

variables

variable

lookupVariableOrNull

makeVar

makeNumVar

makeIntVar

makeBoolVar

numConstraints

constraints

constraint

lookupConstraintOrNull

makeConstraint

makeConstraint

makeConstraint

makeConstraint

objective

solve

solve

write

computeConstraintActivities

verifySolution

reset

interruptSolve

setSolverSpecificParametersAsString

infinity

enableOutput

suppressOutput

iterations

nodes

solverVersion

computeExactConditionNumber

setTimeLimit

wallTime

loadModelFromProto

loadModelFromProtoKeepNames

loadModelFromProtoWithUniqueNamesOrDie

exportModelToProto

createSolutionResponseProto

loadSolutionFromProto

solveWithProto

exportModelAsLpFormat

exportModelAsLpFormat

exportModelAsMpsFormat

exportModelAsMpsFormat

setHint

setNumThreads