XPRESS Options#
ampl: option solver xpress; # change the solver
ampl: option xpress_options 'option1=value1 option2=value2'; # specify options
ampl: solve; # solve the problem
Solver options obtained with $ xpress -=.
XPRESS Optimizer Options for AMPL
--------------------------------------------
To set these options, assign a string specifying their values to the AMPL
option "xpress_options". For example:
ampl: option xpress_options 'mipgap=1e-6';
Options:
acc:_all
Solver acceptance level for all constraints and expressions. Value
meaning: as described in the specific acc:... options.
Can be useful to disable all reformulations (acc:_all=2), or force
linearization (acc:_all=0.)
acc:abs
Solver acceptance level for 'AbsConstraint' as flat constraint, default
2:
0 - Not accepted natively, automatic redefinition will be attempted
1 - Accepted but automatic redefinition will be used where possible
2 - Accepted natively and preferred
acc:acos
Solver acceptance level for 'AcosConstraint' as flat constraint, default
1:
0 - Not accepted natively, automatic redefinition will be attempted
1 - Accepted but automatic redefinition will be used where possible
2 - Accepted natively and preferred
acc:acosh
Solver acceptance level for 'AcoshConstraint' as flat constraint,
default 1:
0 - Not accepted natively, automatic redefinition will be attempted
1 - Accepted but automatic redefinition will be used where possible
2 - Accepted natively and preferred
acc:and (acc:forall)
Solver acceptance level for 'AndConstraint' as flat constraint, default
2:
0 - Not accepted natively, automatic redefinition will be attempted
1 - Accepted but automatic redefinition will be used where possible
2 - Accepted natively and preferred
acc:asin
Solver acceptance level for 'AsinConstraint' as flat constraint, default
1:
0 - Not accepted natively, automatic redefinition will be attempted
1 - Accepted but automatic redefinition will be used where possible
2 - Accepted natively and preferred
acc:asinh
Solver acceptance level for 'AsinhConstraint' as flat constraint,
default 1:
0 - Not accepted natively, automatic redefinition will be attempted
1 - Accepted but automatic redefinition will be used where possible
2 - Accepted natively and preferred
acc:atan
Solver acceptance level for 'AtanConstraint' as flat constraint, default
1:
0 - Not accepted natively, automatic redefinition will be attempted
1 - Accepted but automatic redefinition will be used where possible
2 - Accepted natively and preferred
acc:atanh
Solver acceptance level for 'AtanhConstraint' as flat constraint,
default 1:
0 - Not accepted natively, automatic redefinition will be attempted
1 - Accepted but automatic redefinition will be used where possible
2 - Accepted natively and preferred
acc:cos
Solver acceptance level for 'CosConstraint' as flat constraint, default
1:
0 - Not accepted natively, automatic redefinition will be attempted
1 - Accepted but automatic redefinition will be used where possible
2 - Accepted natively and preferred
acc:cosh
Solver acceptance level for 'CoshConstraint' as flat constraint, default
1:
0 - Not accepted natively, automatic redefinition will be attempted
1 - Accepted but automatic redefinition will be used where possible
2 - Accepted natively and preferred
acc:div
Solver acceptance level for 'DivConstraint' as flat constraint, default
1:
0 - Not accepted natively, automatic redefinition will be attempted
1 - Accepted but automatic redefinition will be used where possible
2 - Accepted natively and preferred
acc:exp
Solver acceptance level for 'ExpConstraint' as flat constraint, default
1:
0 - Not accepted natively, automatic redefinition will be attempted
1 - Accepted but automatic redefinition will be used where possible
2 - Accepted natively and preferred
acc:expa (acc:expA)
Solver acceptance level for 'ExpAConstraint' as flat constraint, default
1:
0 - Not accepted natively, automatic redefinition will be attempted
1 - Accepted but automatic redefinition will be used where possible
2 - Accepted natively and preferred
acc:indeq (acc:indlineq)
Solver acceptance level for 'IndicatorConstraintLinEQ' as flat
constraint, default 2:
0 - Not accepted natively, automatic redefinition will be attempted
1 - Accepted but automatic redefinition will be used where possible
2 - Accepted natively and preferred
acc:indge (acc:indlinge)
Solver acceptance level for 'IndicatorConstraintLinGE' as flat
constraint, default 2:
0 - Not accepted natively, automatic redefinition will be attempted
1 - Accepted but automatic redefinition will be used where possible
2 - Accepted natively and preferred
acc:indle (acc:indlinle)
Solver acceptance level for 'IndicatorConstraintLinLE' as flat
constraint, default 2:
0 - Not accepted natively, automatic redefinition will be attempted
1 - Accepted but automatic redefinition will be used where possible
2 - Accepted natively and preferred
acc:lineq
Solver acceptance level for 'LinConEQ' as flat constraint, default 2:
0 - Not accepted natively, automatic redefinition will be attempted
1 - Accepted but automatic redefinition will be used where possible
2 - Accepted natively and preferred
acc:linge
Solver acceptance level for 'LinConGE' as flat constraint, default 2:
0 - Not accepted natively, automatic redefinition will be attempted
1 - Accepted but automatic redefinition will be used where possible
2 - Accepted natively and preferred
acc:linle
Solver acceptance level for 'LinConLE' as flat constraint, default 2:
0 - Not accepted natively, automatic redefinition will be attempted
1 - Accepted but automatic redefinition will be used where possible
2 - Accepted natively and preferred
acc:log
Solver acceptance level for 'LogConstraint' as flat constraint, default
1:
0 - Not accepted natively, automatic redefinition will be attempted
1 - Accepted but automatic redefinition will be used where possible
2 - Accepted natively and preferred
acc:max
Solver acceptance level for 'MaxConstraint' as flat constraint, default
2:
0 - Not accepted natively, automatic redefinition will be attempted
1 - Accepted but automatic redefinition will be used where possible
2 - Accepted natively and preferred
acc:min
Solver acceptance level for 'MinConstraint' as flat constraint, default
2:
0 - Not accepted natively, automatic redefinition will be attempted
1 - Accepted but automatic redefinition will be used where possible
2 - Accepted natively and preferred
acc:or (acc:exists)
Solver acceptance level for 'OrConstraint' as flat constraint, default
2:
0 - Not accepted natively, automatic redefinition will be attempted
1 - Accepted but automatic redefinition will be used where possible
2 - Accepted natively and preferred
acc:powconstexp
Solver acceptance level for 'PowConstExpConstraint' as flat constraint,
default 1:
0 - Not accepted natively, automatic redefinition will be attempted
1 - Accepted but automatic redefinition will be used where possible
2 - Accepted natively and preferred
acc:quadeq
Solver acceptance level for 'QuadConEQ' as flat constraint, default 2:
0 - Not accepted natively, automatic redefinition will be attempted
1 - Accepted but automatic redefinition will be used where possible
2 - Accepted natively and preferred
acc:quadge
Solver acceptance level for 'QuadConGE' as flat constraint, default 2:
0 - Not accepted natively, automatic redefinition will be attempted
1 - Accepted but automatic redefinition will be used where possible
2 - Accepted natively and preferred
acc:quadle
Solver acceptance level for 'QuadConLE' as flat constraint, default 2:
0 - Not accepted natively, automatic redefinition will be attempted
1 - Accepted but automatic redefinition will be used where possible
2 - Accepted natively and preferred
acc:sin
Solver acceptance level for 'SinConstraint' as flat constraint, default
1:
0 - Not accepted natively, automatic redefinition will be attempted
1 - Accepted but automatic redefinition will be used where possible
2 - Accepted natively and preferred
acc:sinh
Solver acceptance level for 'SinhConstraint' as flat constraint, default
1:
0 - Not accepted natively, automatic redefinition will be attempted
1 - Accepted but automatic redefinition will be used where possible
2 - Accepted natively and preferred
acc:sos1
Solver acceptance level for 'SOS1Constraint' as flat constraint, default
2:
0 - Not accepted natively, automatic redefinition will be attempted
1 - Accepted but automatic redefinition will be used where possible
2 - Accepted natively and preferred
acc:sos2
Solver acceptance level for 'SOS2Constraint' as flat constraint, default
2:
0 - Not accepted natively, automatic redefinition will be attempted
1 - Accepted but automatic redefinition will be used where possible
2 - Accepted natively and preferred
acc:tan
Solver acceptance level for 'TanConstraint' as flat constraint, default
1:
0 - Not accepted natively, automatic redefinition will be attempted
1 - Accepted but automatic redefinition will be used where possible
2 - Accepted natively and preferred
acc:tanh
Solver acceptance level for 'TanhConstraint' as flat constraint, default
1:
0 - Not accepted natively, automatic redefinition will be attempted
1 - Accepted but automatic redefinition will be used where possible
2 - Accepted natively and preferred
alg:addcutoff (addcutoff, mipaddcutoff)
Amount to add to the objective function of the best integer
solution found to give the new MIP cutoff; default -1e-5.
alg:barrier (barrier)
Solve (MIP node) LPs by barrier method.
alg:basis (basis)
Whether to use or return a basis:
0 - No
1 - Use incoming basis (if provided)
2 - Return final basis
3 - Both (1 + 2 = default)
alg:clamping (clamping)
Control adjustements of the returned solution values such that they are
always within bounds:
-1 - Determined automatically
0 - Adjust primal solution to always be within primal bounds (default)
1 - Adjust primal slack values to always be within constraint bounds
2 - Adjust dual solution to always be within the dual bounds implied
by the slacks
3 - Adjust reduced costs to always be within dual bounds implied by
the primal solution
alg:cutoff (cutoff)
If the optimal objective value is worse than cutoff, report "objective
cutoff" and do not return a solution. Default: 1.0E+40 for minimizing,
-1.0E+40 for maximizing.
alg:dual (dual)
Solve (MIP node) LPs by dual simplex method.
alg:feastol (feastol)
Primal feasibility tolerance (default 1e-6).
alg:feastolperturb (feastolperturb)
How much a feasible primal basic solution is allowed to be perturbed
when performing basis changes. The tolerance specified by "alg:feastol"
is always considered as an upper limit for the perturbations; default =
1.0E-06
alg:feastoltarget (feastoltarget)
Specifies the target feasibility tolerance for the solution refiner.
Default = 0 (use the value of "alg:feastol")
alg:iisfind (iisfind, iis)
Whether to find and export an IIS. Default = 0 (don't export).
alg:indlinbigm (indlinbigm)
Largest "big M" value to use in converting indicator constraints to
regular constraints, default = 1e5
alg:lpfolding (lpfolding)
Simplex and barrier: whether to fold an LP problem before solving it:
.. value-table:
alg:maxiis (maxiis)
Maximum number of IIS to find; default=-1 (no limit)
alg:method (method, lpmethod, defaultalg)
Which algorithm to use for non-MIP problems or for node relaxations of
MIP problems, unless barrier/primal/dual/network specified:
1 - Automatic choice (default)
2 - Dual simplex
3 - Primal simplex
4 - Netwon Barrier
alg:network (network)
Solve (substructure of) (MIP node) LPs by network simplex method.
alg:primal (primal)
Solve (MIP node) LPs by primal simplex method.
alg:randomseed (randomseed)
Sets the initial seed to use for the pseudo-random number generator in
the Optimizer; default=1
alg:refactor (refactor)
Whether the optimization should restart using the current representation
of the factorization in memory:
-1 - Automatic choice (default)
0 - No
1 - Yes.
alg:refineops (refineops)
Bit vector: specifies wmhen the solution refiner should be executed to
reduce solution infeasibilities. The refiner will attempt to satisfy the
target tolerances for all original linear constraints before presolve or
scaling has been applied:
1 - refine optimal LP solutions
2 - refine MIP solutions
8 - refine each node of the search tree
16 - refine non-global solutions
32 - apply the iterative refiner to refine the solution
64 - use higher precision in the iterative refinement
128 - iterative refiner will use the primal simplex algorithm
256 - iterative refiner will use the dual simplex algorithm
512 - refine MIP solutions such that rounding them keeps the problem
feasible when reoptimized
1024 - ttempt to refine MIP solutions such that rounding them keeps the
problem feasible when reoptimized, but accept integers solutions
even if refinement fails
alg:relax (relax)
0*/1: Whether to relax integrality of variables.
alg:relcutoff (relcutoff, miprelcutoff)
If the optimal objective value is (relatively) worse than relcutoff,
report "objective cutoff" and do not return a solution. Default: 1.0E-4.
alg:resourcestrategy (resourcestrategy)
Wether to allow nondeterministic decisions to cope with low memory
(affected by maxmemory and maxmemoryhard):
0 - No (default)
1 - Yes.
alg:start (warmstart)
Whether to use incoming primal (and dual, for LP) variable values in a
warmstart:
0 - No
1 - Yes (for LP: if there is no incoming alg:basis) (default)
2 - Yes (for LP: ignoring the incoming alg:basis, if any.)
alg:zerotol (matrixtol)
The zero tolerance on matrix elements. If the value of a matrix element
is less than or equal to this in absolute value, it is treated as zero,
default=1e-9.
bar:alg (baralg)
Which barrier algorithm to use
bar:cachesize (cachesize)
Newton Barrier: L2 or L3 (see notes) cache size in kB (kilobytes) of the
CPU (default -1). On Intel (or compatible) platforms a value of -1 may
be used to determine the cache size automatically.
bar:choleskyalg (choleskyalg)
Type of Cholesky factorization used for barrier, sum of:
:
bar:choleskytol (choleskytol)
Zero tolerance for Cholesky pivots in the
Newton Barrier algorithm; default = 1e-15
bar:cores (barcores)
If positive, number of CPU cores to assume present when using the
barrier algorithm. Default = -1, which means automatic choice
bar:corespercpu (corespercpu)
Newton Barrier: number of cores to assume per cpu. Barrier cache =
cachesize/corespercpu. Default -1 = automatic.
bar:cpuplatform (cpuplatform)
Which instruction are allowed to the Newton barrier method:
:
bar:crash (barcrash)
Choice of crash procedure for crossover, higher number means more
aggressive procedure:
bar:crossover (crossover)
How to transform a barrier solution to a basic one:
-1 - automatic choice (default)
0 - none: return an interior solution
1 - primal crossover first
2 - dual crossover first
bar:crossoverops (crossoverops)
Bit vector affecting crossover after the barrier algorithm; sum of:
1 - return the barrier solution (rather than the last intermediate
solution) when crossover stop early
2 - skip the second crossover stage
4 - skip pivots that are "less numerically reliable"
8 - do a slower but more numerically stable crossover
bar:crossoverthreads (crossoverthreads)
Limit on threads used during crossover; default -1 (determined by
bar:threads).
bar:crossovertol (crossovertol, crossoveraccuracytol)
Tolerance (default 1e-6) for deciding whether to adjust the relative
pivot tolerance during crossover when a new basis factorization is
necessary. Errors in the recalculated basic solution above this
tolerance cause the pivot tolerance to be adjusted.
bar:densecollimit (densecollimit)
Number of nonzeros above which a column is treated as dense in the
barrier algorithm's Cholesky factorization. Default=0 (automatic).
bar:dualstop (bardualstop)
Barrier method convergence tolerance on dual infeasibilities; default =
0 (automatic choice)
bar:gap (bargaptarget)
Barrier algorithm target tolerance for the relative duality gap.If not
satisfied and no further progress is possible but barstopgap is
satisfied, then the current solution is considered optimal.
bar:gapstop (bargapstop)
Barrier method convergence tolerance on the relative duality gap;
default = 0
bar:hgextrapolate (barhgextrapolate)
Extrapolation parameter for the hybrid gradient algorithm; default =
0.99
bar:hgmaxrestarts (barhgmaxrestarts)
Maximum number of restarts in the hybrid gradient algorithm; default
=500
bar:hgops (barhgops)
Control option for hybrid gradient (default = 8); sum of:
1 - use an asymmetric average for the primal averaging
2 - use the 1-norm of the coefficient matrix in normalizing the
initial solution
4 - use the 2-norm of the coefficient matrix in normalizing the
initial solution
8 - use the infinity norm of the coefficient matrix in normalizing the
initial solution
16 - take the square root of omega
32 - contract omega towards 1 if the infeasibility is small enough
64 - omega is based on the infeasibility
bar:indeflimit (barindeflimit)
Maximum indefinite factorizations to allow in the barrier algorithm for
solving a QP: stop when the limit is hit default = 15
bar:kernel (barkernel)
How the barrier algorithm weights centrality:
>= +1.0 - More emphasis on centrality (default 1.0)
<= -1.0 - Each iteration, adaptively select a value from [+1,
-barkernel]
bar:l1cache (l1cache)
Newton barrier: L1 cache size in kB (kilo bytes) of the CPU. On Intel
(or compatible) platforms a value of -1 may be used to determine the
cache size automatically.
bar:objperturb (barobjperturb)
Defines how the barrier perturbs the objective (default 1e-6); values >
0 let the optimizer decide if to perturb the objective, values < 0 force
the perturbation:
n > 0 - automatic decison, scale n
n = 0 - turn off perturbation
n < 0 - force perturbation by abs(n)
bar:objscale (barobjscale)
How the barrier algorithm scales the objective; when the objective is
quadratic, the quadratic diagonal is used in determining the scale:
-1 - Automatic choice (default)
0 - Scale by the geometric mean of the objective coefficients
> 0 - Scale so the argest objective coefficient in absolute value is <=
barobjscale.
bar:order (barorder)
Cholesky factorization pivot order for barrier algorithm:
0 - automatic choice(default)
1 - minimum degree
2 - minimum local fill
3 - nested dissection
bar:orderthreads (barorderthreads)
Number of threads to use when choosing a pivot order for Cholesky
factorization; default 0 (automatic choice).
bar:output (baroutput)
Amount of output for the barrier method:
0 - no output
1 - each iteration (default)
bar:presolve (barpresolve)
Level of barrier-specific presolve effort:
0 - no output
1 - each iteration (default)
bar:primalstop (barprimalstop)
Barrier method convergence tolerance on primal infeasibilities; default
= 0 (automatic choice)
bar:refiter (barrefiter)
Maximum number of refinement iterations, helpful when the the solution
is near to the optimum using barrier or crossover:
0 - default
n > 0 - perform n refinement iterations
bar:regularize (barreg, barrregularize)
Regularization to use with "barrier. Default=-1 (automatic choice), else
sum of:
1 - use "standard" regularization
2 - use "reduced" regularization: less perturbation than "standard"
regularization
4 - keep dependent rows in the KKT system
8 - keep degenerate rows in the KKT system
bar:start (barstart)
Choice of starting point for barrier method:
-1 - Use incoming solution for warm start
0 - Automatic choice (default)
1 - Heuristics based on magnitudes of matrix entries
2 - Use pseudoinverse of constraint matrix
3 - Unit starting point for homogeneous self - dual barrier algorithm.
bar:stepstop (barstepstop)
Barrier method convergence tolerance: stop when step size <=
barstepstop; default = 1e-10
bar:threads (threads)
number of threads used in the Newton Barrier algorithm;
default = -1 (determined by "threads")
cut:cover (covercuts)
The number of rounds of lifted cover inequalities at the top
node.Default=-1, automatic.
cut:depth (cutdepth)
Maximum MIP tree depth at which to generate cuts. Default -1
(automatic); a value of 0 will disable cuts generation.
cut:factor (cutfactor)
Limit on number of cuts and cut coefficients added while solving MIPs.
Default=-1 (automatic); a value of 0 will disable cuts generation.
cut:freq (cutfreq)
Cuts are only generated at tree depths that are integer
multiples of cutfreq. Default=-1 (automatic choice).
cut:gomory (gomcuts)
The number of rounds of Gomory or lift-and-project cuts at the top
node.Default=-1, automatic.
cut:lnpbest (lnpbest)
Number of infeasible global entities to create lift-and-project cuts for
during each round of Gomory cuts at the top node
cut:lnpiterlimit (lnpiterlimit)
Number of iterations to perform in improving each lift-and-project cut;
default=-1 (automatic)
cut:qccuts (qccuts)
when using miqcpalg=1 to solve a mixed-integer problem that has
quadratic constraints or second-order cone constraints, the number of
rounds of outer approximation cuts at the top node; default = -1
(automatic choice).
cut:rltcuts (rltcuts)
Determines whether RLT cuts should be separated in the global solver:
-1 - Automatic choice (default)
0 - No
1 - Yes.
cut:select (cutselect)
Detailed control of cuts at MIP root node; sum of:
32 - clique cuts
64 - mixed - integer founding(MIR) cuts
128 - lifted cover cuts
2048 - flow path cuts
4096 - implication cuts
8192 - automatic lift - and -project strategy
16384 - disable cutting from cut rows
32768 - lifted GUB cover cuts
65536 - zero - half cuts
131072 - indicator - constraint cuts
-1 - all available cuts(default)
cut:strategy (cutstrategy)
How aggressively to generate MIP cuts; more ==> fewer nodes but more
time per node:
-1 - automatic (default)
0 - no cuts
1 - conservative strategy
2 - moderate strategy
3 - aggressive strategy
cut:treecover (treecovercuts)
The number of rounds of lifted cover inequalities at MIP nodes other
than the top node. Default=-1 (automatic).
cut:treegomory (treegomcuts)
The number of rounds of Gomory or lift-and-project cuts at MIP nodes
other than the top node. Default=-1 (automatic).
cut:treeqccuts (treeqccuts)
when using miqcpalg=1 to solve a MIP that has quadratic constraints or
second-order cone constraints, the number of rounds of outer
approximation cuts during the tree search; default = -1 (automatic
choice).
cut:treeselect (treecutselect)
Detailed control of cuts created during the tree search; sum of:
32 - clique cuts
64 - mixed - integer founding(MIR) cuts
128 - lifted cover cuts
2048 - flow path cuts
4096 - implication cuts
8192 - automatic lift - and -project strategy
16384 - disable cutting from cut rows
32768 - lifted GUB cover cuts
65536 - zero - half cuts
131072 - indicator - constraint cuts
-1 - all available cuts(default)
cvt:bigM (cvt:bigm, cvt:mip:bigM, cvt:mip:bigm)
Default value of big-M for linearization of logical constraints. Not
used by default. Use with care (prefer tight bounds). Should be smaller
than (1.0 / [integrality tolerance])
cvt:expcones (expcones)
0*/1: Recognize exponential cones.
cvt:mip:eps (cvt:cmp:eps, cmp:eps)
Tolerance for strict comparison of continuous variables for MIP. Applies
to <, >, and != operators. Also applies to negation of conditional
comparisons: b==1 <==> x<=5 means that with b==0, x>=5+eps. Default:
1e-4.
cvt:names (names, modelnames)
Whether to read or generate variable / constraint / objective names:
0 - No names
1 - (Default) Only provide names if at least one of .col / .row name
files was written by AMPL (AMPL: `option [<solver>_]auxfiles rc;`)
2 - Read names from AMPL, but create generic names if not provided
3 - Create generic names.
cvt:plapprox:domain (plapprox:domain, plapproxdomain)
For piecewise-linear approximated functions, both arguments and result
are bounded to +-[pladomain]. Default 1e6.
cvt:plapprox:reltol (plapprox:reltol, plapproxreltol)
Relative tolerance for piecewise-linear approximation. Default 0.01.
cvt:pre:all
0/1*: Set to 0 to disable most presolve in the flat converter.
cvt:pre:eqbinary
0/1*: Preprocess reified equality comparison with a binary variable.
cvt:pre:eqresult
0/1*: Preprocess reified equality comparison's decidable cases.
cvt:pre:ineqresult
0/1*: Preprocess reified inequality comparison's decidable cases.
cvt:pre:ineqrhs
0/1*: Preprocess reified inequality comparison's right-hand sides.
cvt:pre:unnest
0/1*: Inline nested expressions, currently Ands/Ors.
cvt:prod (cvt:pre:prod)
Product preprocessing flags. Sum of a subset of the following bits:
1 - Quadratize higher-order products in the following order: integer
terms first, then real-valued ones; in each group, smaller-range terms
first.
2 - Logicalize products of 2 binary terms. Logicalizing means that the
product is converted to a conjunction. If the solver does not support it
natively (see acc:and), the conjunction is linearized.
4 - Logicalize products of >=3 binary terms.
Default: 5.
Bits 2 or 4 imply bit 1.
cvt:quadcon (passquadcon)
Convenience option. Set to 0 to disable quadratic constraints. Synonym
for acc:quad..=0. Currently this disables out-multiplication of
quadratic terms, then they are linearized.
cvt:quadobj (passquadobj)
0/1*: Pass quadratic objective terms to the solver. If the solver
accepts quadratic constraints, such a constraint will be created with
those, otherwise linearly approximated.
cvt:socp (socpmode, socp)
Second-Order Cone recognition mode:
0 - Do not recognize SOCP forms
1 - Recognize from non-quadratic expressions only (sqrt, abs)
2 - Recognize from quadratic and non-quadratic SOCP forms. Helpful if
the solver does not recognize non-standard forms
Recognized SOCP forms can be further converted to (SOCP-standardized)
quadratic constraints, see cvt:socp2qc. Default: 1.
cvt:socp2qc (socp2qcmode, socp2qc)
Mode to convert recognized SOCP forms to SOCP-standardized quadratic
constraints:
0 - Do not convert
1 - Convert if no other cone types found, and not all original
quadratics could be recognized as SOC, in particular if the
objective is quadratic
2 - Always convert
Such conversion can be necessary if the solver does not accept a mix of
conic and quadratic constraints/objectives. Default: 2.
cvt:sos (sos)
0/1*: Whether to honor declared suffixes .sosno and .ref describing SOS
sets. Each distinct nonzero .sosno value designates an SOS set, of type
1 for positive .sosno values and of type 2 for negative values. The .ref
suffix contains corresponding reference values used to order the
variables.
cvt:sos2 (sos2)
0/1*: Whether to honor SOS2 constraints for nonconvex piecewise-linear
terms, using suffixes .sos and .sosref provided by AMPL.
cvt:uenc:negctx:max (uenc:negctx:max, uenc:negctx)
If cvt:uenc:ratio applies, max number of constants in comparisons
x==const in negative context (equivalently, x!=const in positive
context) to skip UEnc(x). Default 1.
cvt:uenc:ratio (uenc:ratio)
Min ratio (ub-lb)/Nvalues to skip unary encoding for a variable x, where
Nvalues is the number of constants used in conditional comparisons
x==const. Instead, indicator constraints (or big-Ms) are used, if
uenc:negctx also applies. Default 0.
lim:bariter (bar:iterlim, bariterlim)
Limit on the number of barrier iterations (default 500).
lim:crossoveriter (bar:crossoveriterlim, crossoveriterlim, crossoveritlim)
Limit on crossover iterations after the barrier algorithm; default =
2147483645
lim:heurdiveiterlimit (heurdepth, mip:heurdiveiterlimit)
Simplex iteration limit for reoptimizing during the diving heuristic;
default = -1 (automatic selection); a value of 0 implies no iteration
limit
lim:iter (lpiterlimit, iterlim)
The maximum number of iterations that will be performed by primal
simplex or dual simplex before the optimization process terminates. For
MIP problems, this is the maximum total number of iterations over all
nodes.
lim:lprefineiter (lprefineiterlimit)
This specifies the simplex iteration limit the solution refiner can
spend in attempting to increase the accuracy of an LP solution;
default=-1 (automatic).
lim:maxcuttime (maxcuttime)
The maximum amount of time allowed for generation of cutting planes and
reoptimization;default=0 (no time limit)
lim:mem (memlimit, maxmemoryhard)
Hard limit (integer number of MB) on memory allocated, causing early
termination if exceeded; default = 0 (no limit)
lim:mipsol (maxmipsol)
Limit on the number of MIP solutions to be found (default no limit).
lim:nodes (nodelim, nodelimit, maxnode)
Maximum MIP nodes to explore (default: 2147483647).
lim:softmem (softmemlimit, maxmemorysoft)
Soft limit (integer number of MB) on memory allocated; default = 0 (no
limit)
lim:soltime (soltimelim, soltimelimit)
Limit on solve time (in seconds; default: no limit) to be applied only
after a solution has been found.
lim:stalltime (maxstalltime)
Maximum time in seconds that the MIP Optimizer will continue to search
for improving solution after finding a new incumbent, default=0 (no
limit)
lim:time (timelim, timelimit)
Limit on solve time (in seconds; default: no limit).
lp:bigm (bigm, bigmpenalty)
Infeasibility penalty to be used if "BigM" method is used; default =
1024
lp:bigmmethod (bigmmethod)
Simplex: This specifies whether to use the "Big M" method, or the
standard phase I (achieving feasibility) and phase II (achieving
optimality). the "Big M" method, the objective coefficients of the
variables are considered during the feasibility phase, possibly leading
to an initial feasible basis which is closer to optimal. The
side-effects involve possible round-off errors.
0 - phase I / II
1 - bigM method (default)
lp:crash (crash)
Simplex: This determines the type of crash used when the algorithm
begins.For primal simplex, the choices are listed below; for dual
simplex the choices follow and are interpreted a bit-vector:
0 - none
1 - one-pass search for singletons
2 - multi-pass search for singletons
3 - multi-pass search including slacks
4 - at most 10 passes, only considering slacks at the end
n>10 - like 4, but at most n-10 passes
0 (dual) - perform standard crash.
1 (dual) - perform additional numerical checks during crash
2 (dual) - extend the set of column candidates for crash
3 (dual) - extend the set of row candidates for crash
4 (dual) - force crash
lp:dualforceparallel (forceparalleldual, dualforceparallel)
Specifies whether the dual simplex solver should always use the parallel
simplex algorithm
lp:dualgradient (dualgradient)
dual simplex pricing strategy:
-1 - automatic (default)
0 - devex
1 - steepest edge
2 - direct steepest edge
3 - sparse devex
lp:dualize (dualize)
Whether to convert the primal problem to its dual and solve the
converted problem:
-1 - automatic (default)
0 - solve the primal problem
1 - solve the dual problem
lp:dualizeops (dualizeops)
When solving the dual problem after deriving it from the primal, whether
to use primal simplex if dual simplex was specified and vice versa:
0 - No
1 - Yes (default)
lp:dualperturb (dualperturb)
Factor by which the problem will be perturbed prior to optimization by
dual simplex. Default -1 (automatic); note that a value of 0 implies no
perturbation
lp:dualstrategy (dualstrategy)
Bit vector controlling the dual simplex strategy (default 1):
1 - switch to primal when dual infeasible
2 - stop the solve instead of switching to primal
4 - use aggressive cut-off in MIP search
8 - use dual simplex to remove cost perturbations
16 - aggressive dual pivoting
32 - keep using dual simplex even when numerically unstable
lp:dualthreads (dualthreads)
Limit on threads used by parallel dual simplex; default -1 (determined
by tech:threads).
lp:etatol (etatol)
Zero tolerance on eta elements, elements of eta vectors whose absolute
value is smaller than etatol are taken to be zero.
lp:invertfreq (invertfreq)
Maximum simplex iterations before refactoring the basis; default -1
(automatic)
lp:invertmin (invertmin)
Minimum simplex iterations before refactoring the basis; default = 3
lp:keepbasis (keepbasis)
Basis choice for the next LP iteration:
0 - ignore previous basis
1 - use previous basis (default)
2 - use previous basis only if the number of basic variables == number
of constraints
lp:keepnrows (keepnrows)
Status for nonbinding rows:
-1 - delete N type rows from the matrix (default)
0 - delete elements from N type rows leaving empty N type rows in the
matrix
1 - keep N type rows
lp:log (lplog)
Frequency of printing simplex iteration log; default = 100.Values n < 0
display detailed outputs every -n iterations.
lp:netstalllimit (netstalllimit)
Limit the number of degenerate pivots of the network simplex algorithmm
before switching to primal or dual:
-1 - automatic (default)
0 - no limit
n > 0 - limit to n network simplex iterations
lp:optimalitytol (optimalitytol)
This is the zero tolerance for reduced costs. On each iteration, the
simplex method searches for a variable to enter the basis which has a
negative reduced cost. The candidates are only those variables which
have reduced costs less than the negative value of optimalitytol;
default=1e-6
lp:optimalitytoltarget (optimalitytoltarget)
Target optimality tolerance for the solution refiner; default=0 (use the
value specified by lp:optimalitytol)
lp:penalty (penalty)
Minimum absolute penalty variable coefficient; default = automatic
choice
lp:pivtol (pivtol, markowitztol)
Markowitz pivot tolerance (default = 0.01)
lp:pricingalg (pricingalg)
Primal simplex pricing method:
-1 - partial pricing
0 - automatic choice (default)
1 - devex pricing
2 - steepest edge
3 - steepest edge with initial weights
lp:primalunshift (primalunshift)
Whether the primal alg. calls the dual to unshift:
0 - No
1 - Yes (default)
lp:relpivottol (relpivottol)
Relative pivot tolerance; default = 1e-6
lp:sifting (sifting)
When using dual simplex, whether to enable sifting, which can speed up
the solve when there are many more variables than constraints:
-1 - Automatic choice (default)
0 - No
1 - Yes.
lp:siftpasses (siftpasses)
Determines how quickly we allow to grow the worker problems during the
sifting algorithm; default 4.
lp:siftpresolveops (siftpresolveops)
Presolve operations for solving the subproblems during sifting:
-1 - use the "presolveops" setting specified for the original problem
>=0 - use the value (see "presolveops" for its semantic)
lp:siftswitch (siftswitch)
Determines which algorithm to use for solving the subproblems during
sifting:
-1 - dual simplex
0 - barrier
>0 - use the barrier algorithm while the number of dual infeasibilities
is larger than this value, otherwise use dual simplex
mip:basis (fixmodel, mip:fix)
Whether to compute duals / basis / sensitivity for MIP models:
0 - No (default)
1 - Yes.
mip:bestbound (bestbound, return_bound)
Whether to return suffix .bestbound for the best known MIP dual bound on
the objective value:
0 - No (default)
1 - Yes.
The suffix is on the objective and problem and is -Infinity for
minimization problems and +Infinity for maximization problems if there
are no integer variables or if a dual bound is not available.
mip:branchchoice (branchchoice)
Control the choice of branching when solving a MIP problem:
0 - explore branch with min.estimate first(default)
1 - explore branch with max.estimate first
2 - if an incumbent solution exists, first explore the branch satisfied
by the incumbent; otherwise use choice 0 (min.est.first).
3 - (default) explore the first branch that moves the branching
variable away from its value at the root node; if the branching
entity is not a simple variable, assume branchchoice=0.
mip:branchdisj (branchdisj)
Whether to branch on general split disjunctions while solving MIPs:
-1 - automatic choice (default)
0 - disabled
1 - cautious strategy : create branches only for general integers with
a wide range
2 - moderate strategy
3 - aggressive strategy : create disjunctive branches for both
binaryand integer variables
mip:branchstructural (branchstructural, branchstruct)
Whether to search for special structure during branch and bound:
-1 - Automatic choice (default)
0 - No
1 - Yes.
mip:breadthfirst (breadthfirst)
Number of MIP nodes included in best-first search before switching to
local-first search; default=11.
mip:components (mipcomponents)
Determines whether disconnected components in a MIP should
be solved as separate MIPs:
-1 - Automatic choice (default)
0 - No
1 - Yes.
mip:concurrentnodes (mipconcurrentnodes)
Node limit to choose the winning solve when concurrent
solves are enabled:
-1 - automatic (default)
n > 0 - number of nodes to complete
mip:concurrentsolves (mipconcurrentsolves)
Select the number of concurrent solves to start for a MIP:
-1 - enabled, the number of concurrent solves depends on mipthreads
0 - disabled (default)
1 - disabled (default)
n > 1 - number of concurrent solves = n
mip:deterministic (deterministic)
Whether a MIP search should be deterministic:
mip:dualreductions (mipdualreductions)
Kinds of dual reductions allowed during branch and bound:
0 - none
1 - all (default)
2 - restrict dual reductions to continuous variables
If poolnbest > 1 is specified, specifying mipdualreductions = 2 might be
prudent.
mip:feasibilityjump (feasibilityjump)
Decides whether to run the Feasibility Jump heuristic at the top node
during branch-and-bound:
-1 - automatic
0 - off
1 - run on models with all integer variables
2 - run if all non-integer variables have bounds [0, 1]
3 - run if all non-integer variables have integer bounds
mip:feasibilitypump (feasibilitypump)
Decides whether to run the Feasibility Pump heuristic at the top node
during branch-and-bound:
-1 - automatic (default)
0 - turned off
1 - always run
2 - run if other heuristics have failed to find an integer solution
mip:gap (mipgap)
Max. relative MIP optimality gap (default 1e-4).
mip:gapabs (mipgapabs)
Max. absolute MIP optimality gap (default 0).
mip:heurbeforelp (heurbeforelp)
Whether primal heuristics should be run before the initial LP relaxation
has been solved:
-1 - Automatic choice (default)
0 - No
1 - Yes.
mip:heurdiverandomize (hdive_rand, heurdiverandomize)
The level of randomization to apply in the diving heuristic; values
range from 0.0=none to 1.0=full.
mip:heurdivesoftrounding (hdive_rounding, heurdivesoftrounding)
Whether to use soft rounding in the MIP diving heuristic (to push
variables to their bounds via the objective rather than fixing them):
-1 - automatic (default)
0 - do not use soft rounding
1 - cautious use
2 - aggressing use
mip:heurdivespeedup (hdive_speed, heurdivespeedup)
Controls tradeoff between speed and solution quality in the diving
heuristic:
.. value-table:
mip:heurdivestrategy (hdive_strategy, heurdivestrategy)
Chooses the strategy for the diving heuristic:
-1 - automatic selection (default)
0 - disable heuristics
1-18 - available pre-set strategies for rounding infeasible global
entities
mip:heuremphasis (heuremphasis)
Chooses the strategy for the diving heuristic:
-1 - default strategy (default)
0 - disable heuristics
1 - focus on reducing the gap early
2 - extremely aggressive heuristics
mip:heurforcespecialobj (heurforcespecobj, heurforcespecialobj)
Whether to use special objective heuristics on large problems and even
if an incumbant exists:
0 - No (default)
1 - Yes.
mip:heurfreq (heurfreq)
During branch and bound, heuristics are applied at nodes whose depth
from the root is zero modulo "heurfreq"; default -1 (automatic).
mip:heursearcheffort (heursearcheffort)
Adjusts the overall level of the local search heuristics; default 1.0
(normal level).
mip:heursearchfreq (heurfreq, heursearchfreq)
Specifies how often the local search heuristic should be run in the
tree:
-1 - automatic (default)
0 - disabled in the tree
n>0 - number of nodes between each run
mip:heursearchrootcutfreq (heurrootcutfreq, heursearchrootcutfreq)
How often to run the local search heuristic while cutting at the root
node:
-1 - automatic (default)
0 - disabled during cutting
n>0 - number cutting rounds between each run
mip:heursearchrootselect (heursearchrootselect)
A bit vector control for selecting which local search heuristics to
apply on the root node of a global solve; default 117:
1 - local search with a large neighborhood. Potentially slow but is
good for finding solutions that differs significantly from the
incumbent
2 - local search with a small neighborhood centered around a node LP
solution
4 - local search with a small neighborhood centered around an integer
solution. This heuristic will often provide smaller, incremental
improvements to an incumbent solution
8 - local search with a neighborhood set up through the combination of
multiple integer solutions.
32 - local search without an objective function
64 - local search with an auxiliary objective function
mip:heursearchtreeselect (heursearchtreeselect)
A bit vector control for selecting which local search heuristics to
apply during the tree search of a global solve, default 17:
1 - local search with a large neighborhood. Potentially slow but is
good for finding solutions that differs significantly from the
incumbent
2 - local search with a small neighborhood centered around a node LP
solution
4 - local search with a small neighborhood centered around an integer
solution. This heuristic will often provide smaller, incremental
improvements to an incumbent solution
8 - local search with a neighborhood set up through the combination of
multiple integer solutions.
32 - local search without an objective function
64 - local search with an auxiliary objective function
mip:heurshiftprop (heurshiftprop)
Determines whether the Shift-and-propagate primal heuristic should be
executed immediately after presolve:
-1 - Automatic choice (default)
0 - No
1 - Yes.
mip:heurthreads (heurtreads)
Number of threads to dedicate to running heuristics on the root node:
mip:historycosts (historycosts)
How to update the pseudo cost for a global entity when a strong branch
or a regular branch is applied:
mip:intfeastol (intfeastol)
Feasibility tolerance for integer variables (default 5e-06).
mip:kappafreq (mipkappafreq)
During branch-and-bound, how often to compute basis condition numbers:
0 - never (default)
1 - every node
n > 1 - once per node at level n of the branch-and-bound tree
When mipkappafreq > 0, a final summary shows the number of sampled nodes
that are:
"stable": kappa < 10^7
"suspicious": 10^7 <= kappa < 10^10
"unstable": 10^10 <= kappa < 10^13
"ill-posed": 10^13 <= kappa.
A "Kappa attention level" between 0 and 1 is also reported. Condition
numbers use the Frobenius norms of the basis and its inverse.
mip:localchoice (localchoice)
when to backtrack between two child nodes during a "dive":
1 - never backtrack from the first child unless it is dropped (i.e., is
infeasible or cut off) (default)
2 - always solve both child nodes before deciding which child to
continue with
3 - automatically determined
mip:log (miplog)
Frequency of printing MIP iteration log; default = -100.Values n < 0
display detailed outputs every -n iterations.
mip:maxlocalbacktrack (maxlocalbacktrack, maxlocalbt)
Max height above current node to look for a local backtrack candidate
node; default=-1(automatic)
mip:maxtasks (maxmiptasks)
Maximum tasks to run in parallel during a MIP solve; default = -1 (use
mip:threads).For mip:maxtasks > 0, branch-and-bound nodes are solved in
a deterministic way, but the barrier algorithm (if used) may cause a
nondeterministic MIP solve unless bar:threads = 1.
mip:miprefineiterlimit (miprefiterlim, miprefineiterlimit)
Max. simplex iterations per reoptimization in MIP refiner when refineops
is 2 or 3; default -1 (automatic).
mip:nodeprobingeffort (nodeprobingeffort)
Multiplier on the default amount of work node probing should do. Setting
the control to zero disables node probing.
mip:nodeselection (nodeselection)
Determines which nodes will be considered for solution once the current
node has been solved:
1 - local first: choose between descendant and sibling nodes if
available; choose from all outstanding nodes otherwise
2 - best first: choose from all outstanding nodes
3 - local depth first: choose between descendant and sibling nodes if
available; choose from the deepest nodes otherwise
4 - best first, then local first: best first is used for the first
BREADTHFIRST nodes, after which local first is used
5 - pure depth first: choose from the deepest outstanding nodes
mip:presolve (mippresolve)
Type of integer processing to be performed. If set to 0, no processing
will be performed (default automatic):
1 - reduced-cost fixing at each node
2 - primal reductions will be performed at each node
8 - allow changing continuous-variable bounds
16 - allow dual reductions
32 - allow global tightening of the problem
64 - use objective function
128 - allow restarting
256 - allow use of symmetry
mip:pseudocost (pseudocost)
Default pseudo-cost assumed for forcing an integer variable
to an integer value; default = 0.01
mip:qcrootalg (qcrootalg)
when using miqcpalg = 1 to solve a mixed - integer problem that has
quadratic constraints or second - order cone constraints, the algorithm
for solving the root node:
-1 - automatic (default)
0 - use barrier
1 - use dual simplex on outer approximation
mip:rampup (miprampup)
Whether to limit the number of parallel tasks
during the ramp-up phase of the parallel MIP algorithm:
-1 - automatic choice (default)
0 - no: use as many tasks as possible
1 - yes, until finished with initial dives
mip:relaxtreememorylimit (relaxtreemem, relaxtreememorylimit)
Fraction of memory limit by which to relax "treememlimit" when too much
structural data appears; default 0.1. Set to 0 to never relax the memory
limit in this way.
mip:restart (miprestart)
Control strategy for in-tree restarts:
-1 - automatic choice (default)
0 - disable in-tree restarts
1 - normal aggressiveness
2 - higher aggressiveness
mip:restartfactor (miprestartfactor)
Fine tune initial conditions to trigger an in-tree restart; values > 1
increase the aggressiveness, < 1 decrease it (default 1.0)
mip:restartgapthreshold (miprestartgapthreshold)
Initial gap threshold to delay in-tree restart; the restart is delayed
if the relative gap is below the threshold (default 0.02)
mip:return_gap (return_mipgap)
Whether to return mipgap suffixes or include mipgap values (|objectve -
.bestbound|) in the solve_message: sum of
1 - Return .relmipgap suffix (relative to |obj|)
2 - Return .absmipgap suffix (absolute mipgap)
4 - Suppress mipgap values in solve_message.
Default = 0. The suffixes are on the objective and problem. Returned
suffix values are +Infinity if no integer-feasible solution has been
found, in which case no mipgap values are reported in the solve_message.
mip:round (round)
Whether to round integer variables to integral values before returning
the solution, and whether to report that the solver returned noninteger
values for integer values: sum of
1 ==> Round nonintegral integer variables
2 ==> Modify solve_result
4 ==> Modify solve_message
Default = 0. Modifications that were or would be made are reported in
solve_result and solve_message only if the maximum deviation from
integrality exceeded mip:round_reptol.
mip:round_reptol (round_reptol)
Tolerance for reporting rounding of integer variables to integer values;
see "mip:round". Default = 1e-9.
mip:sbbest (sbbest)
Number of infeasible global entities to initialize pseudo costs for on
each node:
-1 - automatic (default)
0 - disable strong branching
n > 1 - perform strong branching on up to n entities at each node
mip:sbeffort (sbeffort)
Adjusts the overall amount of effort when using strong branching to
select an infeasible global entity to branch on; default = 1.
mip:sbestimate (sbestimate)
How to compute pseudo costs from the local node when selecting an
infeasible entity to branch on:
-1 - automatic (default)
1-6 - different variants of local pseudo costs.
mip:sbiterlimit (sbiterlimit)
Number of dual iterations to perform the strong branching; 0=none,
default = -1 (automatic choice)
mip:sbselect (sbselect)
size of candidate list for strong branching:
-2 - automatic - low effort (default)
-1 - automatic - high effort
n > 0 - include max(n, sbbest) candidates
mip:symmetry (symmetry)
Amount of effort to detect symmetry in MIP problems:
0 - no simmetry detection
1 - conservative effort
2 - intensive effort
mip:symselect (symselect)
Adjusts the overall amount of effort for symmetry detection:
0 - search the whole matrix (otherwise the 0, 1 and -1 coefficients
only)
1 - search all entities(otherwise binaries only)
mip:threads (mipthreads)
Determines the number of threads implemented to run the parallel MIP
code; default -1: alg:threads will determine the number of threads.
mip:toltarget (miptoltarget)
Value of miptol used for refining equalities on MIP problems when
refineops is 2 or 3; default = 0.
mip:varselection (varselection)
How to score the integer variables at a MIP node, for branching on a
variable with minimum score:
- 1 - automatic choice(default)
1 - minimum of the 'up' and 'down' pseudo - costs
2 - 'up' pseudo - cost + 'down' pseudo - cost
3 - maximum of the 'up' and 'down' pseudo - costs plus twice their
minimum
4 - maximum of the 'up' and 'down' pseudo - costs
5 - the 'down' pseudo - cost
6 - the 'up' pseudo - cost
7 - weighted combination of the 'up' and 'down' pseudo costs
8 - product of 'up' and 'down' pseudo costs
obj:multi (multiobj)
Whether to use multi-objective optimization:
0 - Single objective, see option obj:no (default)
1 - Multi-objective, solver's native handling if available
2 - Multi-objective, force emulation
When obj:multi>0 and several objectives are present, suffixes
.objpriority, .objweight, .objreltol, and .objabstol on the objectives
are relevant. Objectives with greater .objpriority values (integer
values) have higher priority. Objectives with the same .objpriority are
weighted by .objweight, according to the option obj:multi:weight.
Objectives with positive .objabstol or .objreltol are allowed to be
degraded by lower priority objectives by amounts not exceeding the
.objabstol (absolute) and .objreltol (relative) limits.
Note that with solver's native handling (when obj:multi=1 and
supported), some solvers might have special rules for the tolerances,
especially for LP, and not allow quadratic objectives. See the solver
documentation.
obj:multi:weight (multiobjweight, obj:multi:weights, multiobjweights)
How to interpret each objective's weight sign:
1 - relative to the sense of the 1st objective
2 - relative to its own sense (default)
With the 1st option (legacy behaviour), negative .objweight for
objective i would make objective i's sense the opposite of the model's
1st objective. Otherwise, it would make objective i's sense the opposite
to its sense defined in the model.
obj:no (objno)
Objective to optimize:
0 - None
1 - First (default, if available)
2 - Second (if available), etc.
pre:basisred (prebasisred)
Determines if a lattice basis reduction algorithm should be attempted as
part of presolve:
-1 - Automatic choice (default)
0 - No
1 - Yes.
pre:bndredcone (prebndredcone)
Determines if second order cone constraints should be used for inferring
bound reductions on variables when solving a MIP:
-1 - Automatic choice (default)
0 - No
1 - Yes.
pre:bndredquad (prebndredquad)
Determines if convex quadratic contraints should be used for inferring
bound reductions on variables when solving a MIP
pre:cliquestrategy (precliquestrategy)
Determines how much effort to spend on clique covers in presolve;
default=-1.
pre:coefelim (precoefelim)
Specifies whether the optimizer should attempt to recombine constraints:
0 - disabled
1 - remove as many coefficients as possible
2 - cautious eliminations
pre:components (precomponents)
Determines whether small independent components should be detected and
solved as individual subproblems during root node processing:
-1 - Automatic choice (default)
0 - No
1 - Yes.
pre:componentseffort (precomponentseffort)
adjusts the overall effort for the independent component presolver;
default = 1.0.
pre:configuration (preconfiguration)
Whether to reformulate binary rows with very few coefficients:
0 - No
1 - Yes (default)
pre:convertseparable (preconvertseparable)
Reformulate problem with non-diagonal quadratic objective and/or
constraints as diagonal quadratic or second-order conic constraints:
-1 - automatic (default)
0 - disable
1 - enable reformulation to diagonal quadratic constraints.
2 - 1, plus reduction to second-order cones
3 - 2, plus the objective function is converted to a constraint and
treated as a quadratic constraint
pre:domcol (predomcol)
Whether presolve should remove variables when solving MIP problems:
-1 - automatic (default)
0 - disable
1 - cautious
2 - aggressive: all candidate will be checked
pre:domrow (predomrow)
Whether presolve should remove constraints when solving MIP problems:
-1 - automatic choice (default)
0 - disabled
1 - cautious
2 - medium
3 - aggressive
pre:duprow (preduprow)
How presolve should deal with duplicate rows in MIP problems:
-1 - automatic (default)
0 - disable
1 - eliminate only rows that are identical in all variables
2 - 1 plus eliminate duplicate rows with simple penalty variable
expressions
3 - 2 plus eliminate duplicate rows with more complex penalty variable
expressions
pre:elimfillin (elimfillin)
Maximum fillins allowed for a presolve elimination; default = 10
pre:elimquad (preelimquad)
Allows for elimination of quadratic variables via doubleton rows:
-1 - Automatic choice (default)
0 - No
1 - Yes.
pre:elimtol (elimtol)
The Markowitz tolerance for the elimination phase of the presolve;
default=0.001
pre:folding (prefolding)
Determines if a folding procedure should be used to aggregate continuous
columns in an equitable partition:
-1 - Automatic choice (default)
0 - No
1 - Yes.
pre:genconsdualreductions (genconsdualreductions)
Whether dual reductions should be applied to reduce the number of
columns and rows added when transforming general constraints to MIP
structs:
0 - No
1 - Yes (default)
pre:implications (preimplications)
Determines whether to use implication structures to remove redundant
rows:
-1 - Automatic choice (default)
0 - No
1 - Yes.
pre:indlinbigm (indprelinbigm)
Largest "big M" value to use in converting indicator constraints to
regular constraints during XPRESS presolve; default = 100.0
pre:lindep (prelindep)
Determines whether to check for and remove linearly dependent equality
constraints when presolving a problem:
-1 - Automatic choice (default)
0 - No
1 - Yes.
pre:maxgrow (presolvemaxgrow)
Limit on how much the number of non-zero coefficients is allowed to grow
during presolve, specified as a ratio of the number of non-zero
coefficients in the original problem; default=0.1
pre:maximpliedbound (maximpliedbound)
When preprocessing MIP problems, only use computed bounds at most
maximpliedbound (default 1e8) in absolute value
pre:maxscalefactor (maxscalefactor)
Maximum log2 factor that can be applied during scaling, must be >=0 and
<=64; default=64.
pre:objcutdetect (preobjcutdetect)
MIP: Determines whether to check for constraints that are parallel or
near parallel to a linear objective function, and which can safely be
removed:
0 - No
1 - Yes (default)
pre:objscalefactor (objscalefactor)
Power of 2 (default 0) by which the objective is scaled. Nonzero
objscalfactor values override automatic global objective scaling
pre:ops (presolveops)
Reductions to use in XPRESS's presolve, sum of:
1 = 2^0 - Remove singleton columns
2 = 2^1 - Remove singleton constraints (rows)
4 = 2^2 - Forcing row removal
8 = 2^3 - Dual reductions
16 = 2^4 - Redundant row removal
32 = 2^5 - Duplicate column removal
64 = 2^6 - Duplicate row removal
128 = 2^7 - Strong dual reductions
256 = 2^8 - Variable eliminations
512 = 2^9 - No IP reductions
1024 = 2^10 - No semi-continuous variable detection
2048 = 2^11 - No advanced IP reductions
4096 = 2^12 - No eliminations on integers
16384 = 2^14 - Linearly dependant row removal
32768 = 2^15 - No integer variable and SOS detection
65536 = 2^16 - No implied bounds
131072 = 2^17 - No clique presolve
262144 = 2^18 - No mod2 presolve
536870912 = 2^29 - No dual reduction on globals
(default 511 = bits 0-8 set)
pre:passes (presolvepasses)
Number of reduction rounds to be performed in presolve; default=1.
pre:permute (prepermute)
Bit vector: specifies whether to randomly permute rows, columns and
global information when starting the presolve (default 0):
1 - permute rows
2 - permute columns
4 - permute global information (for MIP)
pre:permuteseed (prepermuteseed)
Sets the seed for the pseudo-random number generator for permuting;
default=0
pre:probing (preprobing)
Amount of probing to perform on binary variables during presolve. This
is done by fixing a binary to each of its values in turn and analyzing
the implications:
-1 - automatic choice (default)
0 - disabled
1 - cautious
2 - medium
3 - aggressive
pre:protectdual (preprotectdual)
Specifies whether the presolver should protect a given dual solution by
maintaining the same level of dual feasibility:
.. value-table:
pre:pwldualreductions (pwldualreductions)
Whether dual reductions should be applied to reduce the number of
columns, rows and SOS-constraints added when transforming piecewise
linear objectives and constraints to MIP structs:
0 - No
1 - Yes (default)
pre:pwlnonconvextransformation (pwlnonconvextransformation)
Reformulation method for piecewise linear constraints at the beginning
of the search:
-1 - automatic (default)
0 - use a formulation based on SOS2-constraints
1 - use a formulation based on binary variables
pre:rootpresolve (rootpresolve)
Whether to presolve after root cutting and heuristics:
-1 - Automatic choice (default)
0 - No
1 - Yes.
pre:scaling (scaling)
Bit vector determining how to scale the constraint matrix before
optimizing:
1 - row scaling
2 - column scaling
4 - row scaling again
8 - maximum
16 - Curtis-Red
32 - 0->geometric mean, 1->maximum element
64 - no special handling for BigM rows
128 - scale objective function for the simplex method
256 - exclude the quadratic part of constraints when calculating
scaling factors
512 - scale before presolve
1024 - do not scale constraints up
2048 - do not scale variables down
4096 - do not apply automatic global objective scaling
8192 - RHS scaling
16384 - disable aggressive quadratic scaling
32768 - explicit linear slack scaling
pre:solve (presolve)
Whether to use Xpress' presolve:
-1 - Presolve applied, but a problem will not be declared infeasible if
primal infeasibilities are detected. The problem will be solved by
the LP optimization algorithm, returning an infeasible solution,
which can sometimes be helpful
0 - No
1 - Yes (default)
2 - Yes, retaining redundant bounds. This can sometimes increase the
efficiency of the barrier algorithm
For nonlinear presolve, see option pre:solve_nlp.
pre:solve_nlp (presolve_nlp, presolve_slp)
Whether to use Xpress' nonlinear presolve:
0 - No
1 - Yes (default)
2 - Low memory presolve. Original problem is not restored by postsolve
and dual solution may not be completely postsolved.
pre:sosreftol (sosreftol)
Minimum relative gap between the ordering values of elements in a
special ordered set; default=1e-6.
pre:trace (trace)
Display the infeasibility diagnosis during presolve:
0 - No (default)
1 - Yes.
qp:eigenvaluetol (eigenvaluetol)
Regard the matrix in a quadratic form as indefinite if its smallest
eigvenalue is < -eigevnaltol; default = 1e-6
qp:miqcpalg (miqcpalg)
Which algorithm is to be used to solve mixed integer quadratic
constrained and mixed integer second order cone problems:
-1 - automatic (default)
0 - barrier
1 - outer approximations
qp:nonconvex (nonconvex)
Determines if the convexity of the problem is checked before
optimization:
0 - No
1 - Yes (default)
qp:repairindefiniteq (repairindefq, repairindefiniteq)
whether to repair indefinite quadratic forms:
0 - yes
1 - no (default)
qp:simplexops (qsimplexops)
Bit vector, controls the behavior of the quadratic simplex solvers:
1 - traditional primal first phase (default)
2 - force Big M primal first phase
4 - force traditional dual first phase
8 - force BigM dual first phase
16 - always use artificial bounds in dual
32 - use original problem basis only when warmstarting the KKT
64 - skip the primal bound flips for ranged primals (might cause more
trouble than good if the bounds are very large)
128 - also do the single pivot crash
256 - do not apply aggressive perturbation in dual
qp:unshift (quadunshift, quadraticunshift)
whether quadratic simplex should do an extra purification after finding
a solution:
-1 - Automatic choice (default)
0 - No
1 - Yes.
sol:chk:fail (chk:fail, checkfail)
Fail on MP solution check violations, with solve result 150.
sol:chk:feastol (sol:chk:eps, chk:eps, chk:feastol)
Absolute tolerance to check objective values, variable and constraint
bounds. Default 1e-6.
sol:chk:feastolrel (sol:chk:epsrel, chk:epsrel, chk:feastolrel)
Relative tolerance to check objective values, variable and constraint
bounds. Default 1e-6.
sol:chk:infeas (chk:infeas, checkinfeas)
Check even infeasible solution condidates, whenever solver reports them.
sol:chk:inttol (sol:chk:inteps, sol:inteps, chk:inttol)
Solution checking tolerance for variables' integrality. Default 1e-5.
sol:chk:mode (solcheck, checkmode, chk:mode)
Solution checking mode. Sum of a subset of the following bits:
1 - Check variable bounds and integrality.
2 - Check original model constraints, as well as any non-linear
expression values reported by the solver.
4 - Check intermediate auxiliary constraints (i.e., those which were
reformulated further).
8 - Check final auxiliary constraints sent to solver.
16 - Check objective values.
32, 64, 128, 256, 512 - similar, but non-linear expressions are
recomputed (vs using their values reported by the solver.)
*Experimental.* This is an idealistic check, because it does not
consider possible tolerances applied by the solver when computing
expression values.
Default: 1+2+512.
sol:chk:prec (chk:prec, chk:precision)
AMPL solution_precision option when checking: number of significant
digits.
sol:chk:round (chk:round, chk:rnd)
AMPL solution_round option when checking: round to this number of
decimals after comma (before comma if negative.)
sol:count (countsolutions)
0*/1: Whether to count the number of solutions and return it in the
".nsol" problem suffix.
sol:pooldualred (pooldualred)
Whether to suppress removal of dominated solutions(via "dual
reductions") when poolstub is specified:
0 - Yes (default, can be expensive)
1 - No
2 - Honor presolveops bit 3 (2^3 = 8)
sol:pooldupcol (pooldupcol)
Whether to suppress duplicate variable removal when poolstub is
specified:
0 - Yes (default, can be expensive)
1 - No
2 - Honor presolveops bit 3 (2^3 = 8)
sol:pooldups (poold/ups)
How poolstub should handle duplicate solutions:
0 - Retain all duplicates
1 - Discard exact matches
2 - Discard exact matches of continuous variables and matches of
rounded values of discrete variables
3 - Discard matches of rounded values of discrete variables (default)
Rounding of discrete variables is affected bypoolmiptol and poolfeastol
sol:poolfeastol (poolfeastol)
Zero tolerance for discrete variables in the solution pool (default
1e-6)
sol:poolmiptol (poolmiptol)
Error (nonintegrality) allowed in discrete variables in the solution
pool (default 5e-6)
sol:poolnbest (poolnbest, poollimit)
Whether the solution pool (see poolstub) should contain inferior
solutions. When poolnbest = n > 1, the solution pool is allowed to keep
the n best solutions.
sol:stub (ams_stub, solstub, solutionstub)
Stub for solution files. If "solutionstub" is specified, found solutions
are written to files ("solutionstub & '1' & '.sol'") ... ("solutionstub
& Current.nsol & '.sol'"), where "Current.nsol" holds the number of
returned solutions. That is, file names are obtained by appending 1, 2,
... "Current.nsol" to "solutionstub".
tech:backgroundselect (backgroundselect)
Select which tasks to run in background jobs;default - 1 ==> automatic
choice. Set to 0 to not to run any task in the background or to 1 to run
the feasibility jump heuristic in the background.
tech:backgroundthreads (backgroundmaxthreads, backgroundthreads)
Limits the number of threads that Xpress will use for jobs in the
background;default - 1 ==> automatic choice.
tech:cputime (cputime)
How time should be measured when timings are reported in the log and
when checking against time limits :
-1 - disable the timer
0 - use elapsed time (default)
1 - use process time
tech:debug (debug)
0*/1: whether to assist testing & debugging, e.g., by outputting
auxiliary information.
tech:globalfileloginterval (globalfileloginterval)
Seconds between additions to the logfile about, additions to the "global
file", a temporary file written during a global search. Default = 60.
tech:globalfilemax (globalfilemax)
Maximum megabytes for temporary files storing the global search tree: a
new file is started if globalfilemax megabytes would be exceeded.
tech:logfile (logfile)
Log file name; default=no file
tech:optionfile (optionfile, option:file)
Name of an AMPL solver option file to read (surrounded by 'single' or
"double" quotes if the name contains blanks). Lines that start with #
are ignored. Otherwise, each nonempty line should contain "name=value",
e.g., "lim:iter=500".
tech:outlev (outlev)
Whether to write xpress log lines (chatter) to stdout and to file:
0 - none
1 - all
2 - information
3 - warnings & errors only (default)
4 - errors
5 - none
tech:sleeponthreadwait (sleeponthreadwait)
Whether threads should sleep while awaiting work:
-1 - automatically determined
0 - no (busy-wait)
>0 - yes (sleep, might add overhead)
tech:threads (threads)
The default number of threads used during optimization.;default - 1 ==>
automatic choice.
tech:timing (timing, tech:report_times, report_times)
0*/1/2: Whether to print and return timings for the run, all times are
wall times. If set to 1, return the solution times in the problem
suffixes 'time_solver', 'time_setup' and 'time', 'time'=
time_solver+time_setup+time_output is a measure of the total time spent
in the solver driver. If set to 2, return more granular times, including
'time_read', 'time_conversion' and 'time_output'.
tech:tunebase (tunerdir, tunebase)
Base name for results of running XPRESS's search for best parameter
settings. The search is run only when tunebase is specified. This
control only defines the root path for the tuner output. For each
problem, the tuner result will be output to a subfolder underneath this
path. For example, by default, the tuner result for a problem called
prob will be located at tuneroutput/prob/
tech:tunename (tunesessionname)
Set problem name within the tuner "tunebase" is specified.
tech:tuneoutput (tuneroutput, tuneoutput)
Output tuner results and logs to the file system when "tunebase" is
specified:
0 - No
1 - Yes (default)
tech:tunerhistory (tunerhistory)
Reuse and append to previous tuner results of the same problem:
0 - Discard any previous result
1 - Append new results but do not reuse them
2 - Reuse and append new results
tech:tunermethod (tunermethod)
Method for tuning when "tunebase" is specified:
- 1 - automatic choice(default)
0 - default LP tuner
1 - default MIP tuner
2 - more elaborate MIP tuner
3 - root - focused MIP tuner
4 - tree - focused MIP tuner
5 - simple MIP tuner
6 - default SLP tuner
7 - default MISLP tuner
8 - MIP tuner using primal heuristics
tech:tunertarget (tunertarget)
What to measure to compare two problem solutions when running the XPRESS
tuner:
- 1 - automatic choice(default)
0 - solution time, then integrality gap
1 - solution time, then best bound
2 - solution time, then best integer solution
3 - the "primal dual integral", whatever that is
4 - just solution time (default for LPs)
5 - just objective value
6 - validation number (probably not relevant)
7 - gap only
8 - best bound only
9 - best integer solution only
10 - best primal integral - only for individual instances
tech:tunerthreads (tunerthreads)
Number of tuner threads to run in parallel; default=-1 (automatic)
tech:tunerverbose (tunerverbose)
whether the tuner should prints detailed information for each run:
0 - No
1 - Yes (default)
tech:tunetimelim (tunermaxtime, tunetimelim, lim:tunetime)
Time limit (in seconds) on tuning when "tunebase" is specified; default
0 (no time limit).
tech:version (version)
Single-word phrase: report version details before solving the problem.
tech:wantsol (wantsol)
In a stand-alone invocation (no "-AMPL" on the command line), what
solution information to write. Sum of
1 - Write ".sol" file
2 - Primal variables to stdout
4 - Dual variables to stdout
8 - Suppress solution message.
tech:writegraph (cvt:writegraph, writegraph, exportgraph)
File to export conversion graph. Format: JSON Lines.
tech:writemodel (tech:writeprob, writeprob, writemodel, tech:exportfile)
Specifies files where to export the model before solving (repeat the
option for several files.) File name extensions can be ".lp[.7z]",
".mps", etc.
To write a model during iterative solve (e.g., with obj:multi=2), use
tech:writemodel:index.
tech:writemodel:index (tech:writeprob:index, writeprobindex, writemodelindex)
During iterative solve (e.g., with obj:multi=2), the iteration before
which to write solver model. 0 means before iteration is initialized;
positive value - before solving that iteration. Default 0.
tech:writemodelonly (justwriteprob, justwritemodel)
Specifies files where to export the model, no solving (option can be
repeated.) File extensions can be ".dlp", ".mps", etc.
tech:writesolution (writesol, writesolution)
Specifies the names of files where to export the solution and/or other
result files in solver's native formats. Option can be repeated. File
name extensions can be ".sol[.tar.gz]", ".json", ".bas", ".ilp", etc.