Parameters

Parameters control the operation of the Gurobi solvers. They must be modified before the optimization begins. While you should feel free to experiment with different parameter settings, we recommend that you leave parameters at their default settings unless you find a compelling reason not to. For a discussion of when you might want to change parameter values, refer to our Parameter Guidelines.

The various Gurobi APIs all provide routines for querying and modifying parameter values. Refer to our Parameter Examples for additional information.

Some of the parameters below are used to configure a client program for use with a Compute Server, a Gurobi Instant Cloud instance, or a token server. Refer to our discussion of empty environments for details.

Termination

These parameters affect the termination of the algorithms. If the algorithm exceeds any of these limits, it will terminate and report a non-optimal termination status (see the Status Code section for further details). Note that the algorithm won’t necessarily stop the moment it hits the specified limit. The termination check may occur well after the limit has been exceeded.

Parameter name	Purpose
BarIterLimit	Barrier iteration limit
BestBdStop	Best objective bound to stop
BestObjStop	Best objective value to stop
Cutoff	Objective cutoff
IterationLimit	Simplex iteration limit
MemLimit	Memory limit
NodeLimit	MIP node limit
SoftMemLimit	Soft memory limit
SolutionLimit	MIP feasible solution limit
TimeLimit	Time limit
WorkLimit	Work limit

Tolerances

These parameters control the allowable feasibility or optimality violations.

Parameter name	Purpose
BarConvTol	Barrier convergence tolerance
BarQCPConvTol	Barrier QCP convergence tolerance
FeasibilityTol	Primal feasibility tolerance
IntFeasTol	Integer feasibility tolerance
MarkowitzTol	Threshold pivoting tolerance
MIPGap	Relative MIP optimality gap
MIPGapAbs	Absolute MIP optimality gap
OptimalityTol	Dual feasibility tolerance
PSDTol	Positive semi-definite tolerance

Simplex

These parameters control the operation of the simplex algorithms.

Parameter name	Purpose
InfUnbdInfo	Generate additional info for infeasible/unbounded models
LPWarmStart	Warm start usage in simplex
NetworkAlg	Network simplex algorithm
NormAdjust	Simplex pricing norm
PerturbValue	Simplex perturbation magnitude
Quad	Quad precision computation in simplex
Sifting	Sifting within dual simplex
SiftMethod	LP method used to solve sifting sub-problems
SimplexPricing	Simplex variable pricing strategy

Barrier

These parameters control the operation of the barrier solver.

Parameter name	Purpose
BarCorrectors	Central correction limit
BarHomogeneous	Barrier homogeneous algorithm
BarOrder	Barrier ordering algorithm
Crossover	Barrier crossover strategy
CrossoverBasis	Crossover initial basis construction strategy
QCPDual	Compute dual variables for QCP models

Scaling

These parameters control the operation of the simplex algorithms and the barrier solver.

Parameter name	Purpose
ObjScale	Objective scaling
ScaleFlag	Model scaling

MIP

These parameters control the operation of the MIP algorithms.

Parameter name	Purpose
BranchDir	Branch direction preference
ConcurrentJobs	Enables distributed concurrent solver
ConcurrentMethod	Chooses continuous solvers to run concurrently
ConcurrentMIP	Enables concurrent MIP solver
ConcurrentSettings	Create concurrent environments from a list of .prm files
DegenMoves	Degenerate simplex moves
DistributedMIPJobs	Enables the distributed MIP solver
Heuristics	Turn MIP heuristics up or down
ImproveStartGap	Trigger solution improvement
ImproveStartNodes	Trigger solution improvement
ImproveStartTime	Trigger solution improvement
LazyConstraints	Programs that add lazy constraints must set this parameter
MinRelNodes	Minimum relaxation heuristic control
MIPFocus	Set the focus of the MIP solver
MIQCPMethod	Method used to solve MIQCP models
NLPHeur	Controls the NLP heuristic for non-convex quadratic models
NodefileDir	Directory for MIP node files
NodefileStart	Memory threshold for writing MIP tree nodes to disk
NodeMethod	Method used to solve MIP node relaxations
NonConvex	Control how to deal with non-convex quadratic programs
NoRelHeurTime	Limits the amount of time (in seconds) spent in the NoRel heuristic
NoRelHeurWork	Limits the amount of work performed by the NoRel heuristic
OBBT	Controls aggressiveness of optimality-based bound tightening
PartitionPlace	Controls when the partition heuristic runs
PumpPasses	Feasibility pump heuristic control
RINS	RINS heuristic
SolFiles	Location to store intermediate solution files
SolutionNumber	Sub-optimal MIP solution retrieval
StartNodeLimit	Node limit for MIP start sub-MIP
StartNumber	Set index of MIP start
SubMIPNodes	Nodes explored by sub-MIP heuristics
Symmetry	Symmetry detection
VarBranch	Branch variable selection strategy
ZeroObjNodes	Zero objective heuristic control

Presolve

These parameters control the operation of the presolve algorithms.

Parameter name	Purpose
AggFill	Allowed fill during presolve aggregation
Aggregate	Presolve aggregation control
DualReductions	Disables dual reductions in presolve
PreCrush	Allows presolve to translate constraints on the original model to equivalent constraints on the presolved model
PreDepRow	Presolve dependent row reduction
PreDual	Presolve dualization
PreMIQCPForm	Format of presolved MIQCP model
PrePasses	Presolve pass limit
PreQLinearize	Presolve Q matrix linearization
Presolve	Presolve level
PreSOS1BigM	Controls largest coefficient in SOS1 reformulation
PreSOS1Encoding	Controls SOS1 reformulation
PreSOS2BigM	Controls largest coefficient in SOS2 reformulation
PreSOS2Encoding	Controls SOS2 reformulation
PreSparsify	Presolve sparsify reduction

Tuning

These parameters control the operation of the parameter tuning tool.

Parameter name	Purpose
TuneBaseSettings	Comma-separated list of base parameter settings
TuneCleanup	Enables a tuning cleanup phase
TuneCriterion	Specify tuning criterion
TuneDynamicJobs	Enables distributed tuning using a dynamic set of workers
TuneJobs	Enables distributed tuning using a static set of workers
TuneMetric	Metric to aggregate results into a single measure
TuneOutput	Tuning output level
TuneResults	Number of improved parameter sets returned
TuneTargetMIPGap	A target gap to be reached
TuneTargetTime	A target runtime in seconds to be reached
TuneTimeLimit	Time limit for tuning
TuneTrials	Perform multiple runs on each parameter set to limit the effect of random noise
TuneUseFilename	Use model file names as model names

Multiple Solutions

These parameters allow you to modify the behavior of the MIP search in order to find more than one solution to a MIP model.

Parameter name	Purpose
PoolGap	Relative gap for solutions in pool
PoolGapAbs	Absolute gap for solutions in pool
PoolSearchMode	Choose the approach used to find additional solutions
PoolSolutions	Number of solutions to keep in pool

MIP Cuts

These parameters affect the generation of MIP cutting planes. In all cases, a value of -1 corresponds to an automatic setting, which allows the solver to determine the appropriate level of aggressiveness in the cut generation. Unless otherwise noted, settings of 0, 1, and 2 correspond to no cut generation, conservative cut generation, or aggressive cut generation, respectively. The Cuts parameter provides global cut control, affecting the generation of all cuts. This parameter also has a setting of 3, which corresponds to very aggressive cut generation. The other parameters override the global Cuts parameter (so setting Cuts to 2 and CliqueCuts to 0 would generate all cut types aggressively, except clique cuts which would not be generated at all).

Parameter name	Purpose
BQPCuts	BQP cut generation
Cuts	Global cut generation control
CliqueCuts	Clique cut generation
CoverCuts	Cover cut generation
CutAggPasses	Constraint aggregation passes performed during cut generation
CutPasses	Root cutting plane pass limit
FlowCoverCuts	Flow cover cut generation
FlowPathCuts	Flow path cut generation
GomoryPasses	Root Gomory cut pass limit
GUBCoverCuts	GUB cover cut generation
ImpliedCuts	Implied bound cut generation
InfProofCuts	Infeasibility proof cut generation
LiftProjectCuts	Lift-and-project cut generation
MIPSepCuts	MIP separation cut generation
MIRCuts	MIR cut generation
MixingCuts	Mixing cut generation
ModKCuts	Mod-k cut generation
NetworkCuts	Network cut generation
ProjImpliedCuts	Projected implied bound cut generation
PSDCuts	PSD cut generation
RelaxLiftCuts	Relax-and-lift cut generation
RLTCuts	RLT cut generation
StrongCGCuts	Strong-CG cut generation
SubMIPCuts	Sub-MIP cut generation
ZeroHalfCuts	Zero-half cut generation

Distributed Algorithms

Parameters that are used to control our distributed parallel algorithms (distributed MIP, distributed concurrent, and distributed tuning).

Parameter name	Purpose
WorkerPassword	Password for distributed worker cluster
WorkerPool	Distributed worker cluster

Instant Cloud

Parameters that are used to launch Gurobi Instant Cloud instances.

Parameter name	Purpose
CloudAccessID	Access ID for Gurobi Instant Cloud
CloudHost	Host for the Gurobi Cloud entry point
CloudSecretKey	Secret Key for Gurobi Instant Cloud
CloudPool	Cloud pool to use for Gurobi Instant Cloud instance

Compute Server

Parameters that are used to configure and launch Gurobi Compute Server jobs. You will normally set these in your license file, but you have the option of setting them through these parameters instead (by first constructing an empty environment). Refer to the Gurobi Remote Services Reference Manual for more information.

Parameter name	Purpose
ComputeServer	Name of a node in the Remote Services cluster.
ServerPassword	Client password for Remote Services cluster (or token server).
ServerTimeout	Network timeout interval
CSPriority	Job priority for Remote Services job
CSQueueTimeout	Queue timeout for new jobs
CSRouter	Router node for Remote Services cluster
CSGroup	Group placement request for cluster
CSTLSInsecure	Use insecure mode in Transport Layer Security (TLS)
CSIdleTimeout	Idle time before Compute Server kills a job
JobID	Job ID of current job

Cluster Manager

Parameters that are used to configure and launch Gurobi Cluster Manager. You will normally set these in your license file, but you have the option of setting them through these parameters instead (by first constructing an empty environment). Refer to the Gurobi Remote Services Reference Manual for more information.

Parameter name	Purpose
CSAPIAccessID	Access ID for Gurobi Cluster Manager
CSAPISecret	Secret key for Gurobi Cluster Manager
CSAppName	Application name of the batches or jobs
CSAuthToken	Token used internally for authentication
CSBatchMode	Controls Batch-Mode optimization
CSClientLog	Turns logging on or off
CSManager	URL for the Cluster Manager
Username	User name to use when connecting to the Cluster Manager

Token Server

Parameters that are used to launch jobs that check out tokens from a token server. You will normally set these in your license file, but you have the option of setting them through these parameters instead (by first constructing an empty environment).

Parameter name	Purpose
ServerPassword	Client password for token server (or Remote Services cluster).
TokenServer	Name of your token server.
TSPort	Token server port number.

Web License Service

Parameters that are used to launch jobs that use the Web License Service (WLS). You will normally set these in your license file, but you have the option of setting them through these parameters instead (by first constructing an empty environment).

Parameter name	Purpose
LicenseID	License ID.
WLSAccessID	WLS access ID.
WLSSecret	WLS secret.
WLSToken	WLS token.
WLSTokenDuration	WLS token duration.
WLSTokenRefresh	Relative WLS token refresh interval.

Other

Other parameters.

Parameter name	Purpose
Disconnected	Disconnected component strategy
DisplayInterval	Frequency at which log lines are printed
FeasRelaxBigM	Big-M value for feasibility relaxations
FuncPieceError	Error allowed for PWL translation of function constraint
FuncPieceLength	Piece length for PWL translation of function constraint
FuncPieceRatio	Controls whether to under- or over-estimate function values in PWL approximation
FuncPieces	Sets strategy for PWL function approximation
FuncMaxVal	Maximum value for x and y variables in function constraints
FuncNonlinear	Chooses the approximation approach used to handle function constraints
IgnoreNames	Indicates whether to ignore names provided by users
IISMethod	IIS method
InputFile	File to be read before optimization commences
IntegralityFocus	Set the integrality focus
JSONSolDetail	Controls the level of detail stored in generated JSON solution
LogFile	Log file name
LogToConsole	Console logging
Method	Algorithm used to solve continuous models
MultiObjMethod	Warm-start method to solve for subsequent objectives
MultiObjPre	Initial presolve on multi-objective models
MultiObjSettings	Create multi-objective settings from a list of .prm files
NumericFocus	Set the numerical focus
ObjNumber	Set index of multi-objectives
OutputFlag	Solver output control
Record	Enable API call recording
ResultFile	Result file written upon completion of optimization
ScenarioNumber	Set index of scenario in multi-scenario models
Seed	Modify the random number seed
SolutionTarget	Specify the solution target for LP
Threads	Number of parallel threads to use
UpdateMode	Change the behavior of lazy updates