To set these directives, assign a string specifying their values to the AMPL option
xpress_options. For example:
ampl: option xpress_options ‘primal presolve=2 feastol=1e-8′;
[no assignment]in the listing.
advance whether to use an initial basis, if available: 0 = no, overriding mipstartstatus; 1 = yes (default), subject to mipstartstatus. In an AMPL session, "option send_statuses 0;" is preferable to "option xpress_options '... advance=0 ...';".
algaftercrossover algorithm for final cleanup after running the barrier algorithm: 1 = automatic choice (default) 2 = dual simplex 3 = primal simplex 4 = concurrent
algafternetwork algorithm for final cleanup after the network simplex algorithm: 1 = automatic choice (default) 2 = dual simplex 3 = primal simplex
autoperturb whether to introduce perturbations when the simplex method encounters too many degenerate pivots: 1 = yes (default); 0 = no
backtrack choice of next node when solving MIP problems: -1 = automatic choice (default) 1 = withdrawn; formerly choice 2 until a feasible integer solution has been found, then Forrest-Hirst-Tomlin choice 2 = node with best estimated solution 3 = node with best bound on the solution (default) 4 = deepest node (depth-first search) 5 = highest node (breadth-first search) 6 = earliest-created node 7 = most recently created node 8 = random choice 9 = node with fewest LP relaxation infeasibilities 10 = combination of 2 and 9 11 = combination of 2 and 4
backtracktie how to break ties for the next MIP node: same choices as for "backtrack"
baralg which barrier algorithm to use with "barrier": -1 = automatic choice (default with just "barrier") 1 = infeasible-start barrier algorithm 2 = homogeneous self-dual barrier algorithm 3 = start with 2 and maybe switch to 1 while solving
barcores if positive, number of CPU cores to assume present when using the barrier algorithm. Default = -1, which means automatic choice.
barcrash choice of crash procedure for crossover: 0 = no crash 1-6 = available strategies (default 4): 1 = most conservative, 6 = most agreessive
bardualstop barrier method convergence tolerance on dual infeasibilities; default = 0 (automatic choice)
bargapstop barrier method convergence tolerance on the relative duality gap; default = 0
barindeflimit maximum indefinite factorizations to tolerate in the barrier algorithm for solving a QP: stop when the limit is hit; default = 15
bariterlimit maximum number of Newton Barrier iterations; default = 500
barobjscale how the barrier algorthm scales the objective: -1 = automatic chocie (default) 0 = scale by the geometric mean of the objective coefficients > 0 = scale so the argest objective coefficient in absolute value is <= barobjscale. When the objective is quadratic, the quadratic diagonal is used in determining the scale.
barorder Cholesky factorization pivot order for barrier algorithm: 0 = automatic choice (default) 1 = minimum degree 2 = minimum local fill 3 = nested dissection
barorderthreads number of threads to use when choosing a pivot order for Cholesky factorization; default 0 ==> automatic choice.
baroutput amount of output for the barrier method: 0 = no output 1 = each iteration (default)
barpresolve level of barrier-specific presolve effort: 0 = use standard presolve (default) 1 = use more effort 2 = do full matrix eliminations for size reduction
barprimalstop barrier method convergence tolerance on primal infeasibilities; default = 0 (automatic choice)
barreg regularization to use with "barrier": -1 = automatic choice (default with just "barrier") Values >= 0 are the 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
barrier [no assignment] use the Newton Barrier algorithm
barstart choice of starting point for barrier method: 0 = automatic choice (default) 1 = heuristics based on magnitudes of matrix entries 2 = use pseudoinverse of constraint matrix
barstepstop barrier method convergence tolerance: stop when step size <= barstepstop; default = 1e-10
barthreads number of threads used in the Newton Barrier algorithm; default = -1 (determined by "threads")
basisin load initial basis from specified file
basisout save final basis to specified file
bestbound [no assignment] return suffix .bestbound for the best known bound on the objective value. The suffix is on the problem and objective and is +Infinity for minimization problems and -Infinity for maximization problems if there are no integer variables or if an integer feasible solution has not yet been found.
bigm infeasibility penalty; default = 1024
bigmmethod 0 = phase I/II, 1 = BigM method (default)
branchchoice whether to explore branch with min. or max. estimate first: 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) default = 3 3 = 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
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 binary and integer variables
branchstruct whether to search for special structure during branch and bound: -1 = automatic choice (default) 0 = no 1 = yes
breadthfirst number of MIP nodes included in best-first search (default 11) before switching to local-first search
cachesize cache size in Kbytes -- relevant to Newton Barrier: -1 = determined automatically default = system-dependent (-1 for Intel)
choleskyalg type of Cholesky factorization used for barrier: sum of 1 ==> manual matrix blocking 2 ==> single pass with manual blocking 4 ==> nonseparable QP relaxation 8 ==> manual corrector weight (honor "16" bit) 16 ==> manual corrector weight "on" 32 ==> manual refinement 64 ==> use preconditioned conjugate gradients 128 ==> refine with QMR (quasi-minimal residual) default = -1 (automatic choice)
choleskytol zero tolerance for Cholesky pivots in the Newton Barrier algorithm; default = 1e-15
concurrentthreads synonym for lpthreads
conedecomp whether to decompose regular and rotated cone constraints having more than two elements and to use the result in an outer approximation: -1 = automatic choice (default) 0 = no 1 = yes, unless the cone variable is fixed by XPRESS's presolve 2 = yes, even if the cone variable is fixed 3 = yes, but only for outer approximations
convexitychk whether to check convexity before solving: 0 = no 1 = yes (default)
corespercpu number of cores to assume per cpu; default = -1 ==> number detected; barrier cache = cachesize / corespercpu
covercuts for MIPS, the number of rounds of lifted-cover inequalities at the top node; default = -1 ==> automatic choice
cpuplatform whether the Newton Barrier method should use AVX or SSE2 instructions on platforms that offer both: -1 = automatic choice (default) 0 = use generic code: neither AVX nor SSE2 1 = use SSE2 2 = use AVX 3 = use AVX2
cputime which times to report when logfile is specified: 0 = elapsed time (default) 1 = CPU time 2 = process time You may need to experiment to see how cputime=1 and cputime=2 differ (if they do) on your system.
crash type of simplex crash: 0 = none 1 = one-pass search for singletons 2 = multi-pass search for singletons (default) 3 = multi-pass search including slacks 4 = at most 10 passes, only considering slacks at the end n = (for n > 10) like 4, but at most n-10 passes
crossover whether to find a simplex basis after the barrier alg.: -1 = automatic choice (default) 0 = no crossover 1 = primal crossover first 2 = dual crossover first
crossovertol 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.
cutdepth maximum MIP tree depth at which to generate cuts: 0 = no cuts -1 = automatic choice (default)
cutfactor limit on number of cuts and cut coefficients added while solving MIPs: -1 = automatic choice (default) 0 = do not add cuts > 0 ==> multiple of number of original constraints
cutfreq MIP cuts are only generated at tree depths that are integer multiples of cutfreq; -1 = automatic choice (default)
cutselect detailed control of cuts at MIP root node: sum of 16 = clique cuts 32 = mixed-integer founding (MIR) cuts 64 = lifted cover cuts 1024 = flow path cuts 2048 = implication cuts 4096 = automatic lift-and-project strategy 8192 = disable cutting from cut rows 16384 = lifted GUB cover cuts -1 = all available cuts (default)
cutstrategy how aggressively to generate MIP cuts; more ==> fewer nodes but more time per node: -1 = automatic choice (default) 0 = no cuts 1 = conservative strategy 2 = moderate strategy 3 = aggressive strategy
defaultalg algorithm to use when none of "barrier", "dual", or "primal" is specified: 1 = automatic choice (default) 2 = dual simplex 3 = primal simplex 4 = Newton Barrier
densecollimit number of nonzeros above which a column is treated as dense in the barrier algorithm's Cholesky factorization: 0 = automatic choice (default)
deterministic whether a MIP search should be deterministic: 0 = no 1 = yes (default)
dual [no assignment] use the dual simplex algorithm
dualgradient dual simplex pricing strategy: -1 = automatic choice 0 = Devex 1 = steepest edge
dualize whether to convert the primal problem to its dual and solve the converted problem: -1 = automatic choice (default) 0 = no: solve primal problem 1 = yes: solve dual problem
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)
dualstrategy how to remove infeasibilities when re-optimizing with the dual algorithm during MIP solves: 0 = use primal algorithm 1 = use dual algorithm (default)
dualthreads limit on number of threads used by parallel dual simplex, overriding "threads"; default -1 ==> use "threads"
eigenvaltol regard the matrix in a quadratic form as indefinite if its smallest eigvenalue is < -eigevnaltol; default = 1e-6
elimtol Markowitz tolerance for the elimination phase of XPRESS's presolve; default = 0.001
etatol zero tolerance on eta elements; default varies with XPRESS version; default = 1e-12 or 1e-13 with some versions. Use etatol=? to see the current value.
feaspump whether to run the Feasibility Pump heuristic at the top node during branch-and-bound: one of 0 = no (default) 1 = yes 2 = only if other heurstics found no integer solution
feastol zero tolerance on RHS; default = 1e-6
feastol_target feasibility tolerance on constraints for solution refiner (see refineops): if feastol_target > 0 is specified, it is used instead of feastol
gomcuts gomory cuts at root: -1 = automatic choice (default)
hdive_rand value between 0 and 1 inclusive affecting randomization in the diving heuristic: 0 (default) ==> none; 1 ==> full; intermediate values ==> intermediate behavior
hdive_rounding 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 choice (default) 0 = no soft rounding 1 = cautious soft rounding 2 = aggressive soft rounding
hdive_speed controls tradeoff between speed and solution quality in the diving heuristic: an integer between -2 and 3: -2 = automatic bias toward quality -1 = automatic bias toward speed (default) 0 = emphasize quality 4 = emphasize speed 1-3 = intermediate emphasis
hdive_strategy strategy for diving heuristic: integer between -1 and 10: -1 = automatic choice (default) 0 = do not use the diving heursistic 1-10 = preset strategies for diving
heurdepth deprecated: no longer has any effect: maximum depth of branch-and-bound tree search at which to apply heuristics; 0 = no heuristics; default = -1
heureffort factor affecting how much work local search heuristics should expend. Default = 1; higher values cause more local searches over larger neighborhoods.
heurfreq during branch and bound, heuristics are applied at nodes whose depth from the root is zero modulo heurfreq; default = -1 (automatic choice)
heurmaxsol deprecated: no longer has any effect: maximum number of heuristic solutions to find during branch- and-bound tree search; default = -1 (automatic choice)
heurnodes deprecated: no longer has any effect: maximum nodes at which to use heuristics during branch-and-bound tree search; default = 1000
heurroot bit vector controlling local search heuristics to apply at the root node: sum of 1 = large-neighborhood search: may be slow, but may find solutions far from the incumbent 2 = small-neighborhood search about node LP solution 4 = small-neighborhood search about integer solutions 8 = local search near multiple integer solutions 16 = no effect 32 = local search without an objective; may only be done when no feasible solution is available default = 53
heurrootcutfreq how often to run the local search heuristic while cutting at the root node: -1 ==> automatic choice (default) 0 ==> never n > 0 ==> do n cutting rounds between runs of the
local search heuristic heursearch how often the local search heurstic should be run during branch-and-bound: -1 = automatic choice (default) 0 = never n > 0 ==> every n nodes
heurstrategy heuristic strategy for branch and bound: one of -1 = automatic choice (default) 0 = no heuristics 1 = basic heuristics 2 = enhanced heuristics 3 = extensive heuristics
heurthreads number of threads for the root node of branch-and-bound: -1 = determined from "threads" keyword 0 = no separate threads (default) n > 0 ==> use n threads
heurtree heuristics to apply during tree search: sum of the same values as for heurroot; default 17
iis [no assignment] if the problem is infeasible, find an Irreducible Independent Set of infeasible constraints and return it in suffix .iis. If changing the bounds on just one constraint or variable could remove the infeasibility, return suffix .iso with value 1 for each such constraint or variable.
indlinbigm largest "big M" value to use in converting indicator constraints to regular constraints; default = 1e5.
indprelinbigm largest "big M" value to use in converting indicator constraints to regular constraints during XPRESS presolve; default = 100.0
invertfreq maximum simplex iterations before refactoring the basis: -1 = automatic choice (default)
invertmin minimum simplex iterations before refactoring the basis: default = 3
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
keepnrows 1 (default) if unconstrained rows are to be kept, else 0
lazy whether to regard constraints with nonzero .lazy suffix values as lazy (i.e., delayed) constraints if the problem is a MIP: 0 = no 1 = yes (default)
lnpbest number of global infeasible entities for which to create lift-and-project cuts during each round of Gomory cuts at the top node; default = 50
lnpiterlimit maximum iterations for each lift-and-project cut; default = -1 (automatic choice)
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) 2 = always solve both nodes first 3 = automatic choice (default)
logfile name of log file; default = no log file
lpiterlimit simplex iteration limit; default = 2147483647 = 2^31 - 1
lplog frequency of printing simplex iteration log; default = 100
lpref_itlim limit on simplex iterations used by the solution refiner (see refineops); default = -1 ==> automatic choice
lpthreads number of threads in concurrent LP solves: -1 = determine from "threads" keyword (default) n > 0 ==> use n threads
markowitztol Markowitz tolerance used when factoring the basis matrix default = 0.01
matrixtol zero tolerance on matrix elements; default = 1e-9
maxcuttime maximum time (CPU seconds) to spend generating cuts and reoptimizing; default = 0 ==> no limit
maxiis maximum number of Irreducible Infeasible Sets to find: -1 = no limit (default) 0 = none
maxim [no assignment] force maximization of the objective
maximise [no assignment] force maximization of the objective
maximize [no assignment] force maximization of the objective
maximpliedbound when preprocessing MIP problems, only use computed bounds at most maximpliedbound (default 1e8) in absolute value
maxlocalbt max height above current node to look for a local backtrack candidate node; default = 1
maxlogscale max log2 of factors used in scaling; must be >= 0 and <= 64; default 64
maxmemory limit (integer number of megabytes) on memory used: -1 = automatic choice (default) >0 = target megabytes of memory to use
maxmipsol maximum number of integer solutions to find: 0 = no limit (default)
maxmiptasks maximum tasks to run in parallel during a MIP solve: -1 ==> use mipthreads n > 0 ==> at most n tasks running at once For maxmiptasks > 0, branch-and-bound nodes are solved in a deterministic way, but the barrier algorithm (if used) may cause a nondeterministic MIP solve unless barthreads = 1.
maxnode maximum number of MIP nodes to explore; default = 2147483647
maxpagelines maximum output lines between page breaks in logfile; default = 23
maxtime maximum solution time allowed; default = 0 ==> no limit
minim [no assignment] force minimization of the objective
minimise [no assignment] force minimization of the objective
minimize [no assignment] force minimization of the objective
mipabscutoff initial MIP cutoff: ignore MIP nodes with objective values worse than mipabscutoff; default = 1e40 for minimization, -1e40 for maximization
mipabsstop stop MIP search if abs(MIPOBJVAL - BESTBOUND) <= mipabsstop default = 0
mipaddcutoff amount to add to the objective function of the best integer solution found to give the new MIP cutoff; default -1e-5
miplog MIP printing level to logfile (default -100): -n = print summary line every n MIP nodes 0 = no MIP summary lines 1 = only print a summary at the end 2 = log each solution found 3 = log each node
mipops MIP solver options: one of 0 = traditional primal first phase (default) 1 = Big M primal first phase 2 = traditional dual first 3 = Big M dual first 4 = always use artificial bounds in dual 5 = use original basis only when warmstarting 6 = skip primal bound flips for ranged primals 7 = also do single-pivot crash 8 = suppress aggressive dual perturbations
mippresolve MIP presolve done at each node: sum of 1 = reduced-cost fixing 2 = logical preprocessing of binary variables 4 = ignored; replaced by "preprobing" 8 = allow changing continuous-variable bounds 16 = allow dual reductions 32 = use objective function default = -1 (automatic choice)
miprefiterlim max. simplex iterations per reoptimization in MIP refiner when refineops is 2 or 3; default -1 ==> automatic choice
miprelcutoff fraction of best integer solution found to add to MIP cutoff; default 1e-4
miprelstop stop MIP search if abs(MIPOBJVAL - BESTBOUND) < miprelstop * abs(BESTBOUND); default = 0.0001
mipstart synonym for mipstartvalue
mipstartstatus whether to use incoming statuses on MIP problems; default 1 ==> yes
mipstartvalue whether to use the specified initial guess (if supplied) when solving a MIP problem: 0 = no 1 = yes (default)
mipstop how to stop a MIP solve when a time or node limit is reached: 0 = stop tasks as soon as possible (default) 1 = let currently running tasks finish, but do not start new ones
mipthreads number of threads to use solving mixed-integer programming problems: -1 = use "threads" keyword (default) n > 0 ==> use n threads
miptol integer feasibility tolerance; default = 5e-6
miptoltarget Value of miptol used for refining equalities on MIP problems when refineops is 2 or 3; default = 0
miqcpalg algorithm for solving mixed-integer problems with quadratic or second-order cone constraints: -1 = automatic choice (default) 0 = barrier algorithm during branch and bound 1 = outer approximations during branch and bound
network [no assignment] try to find and exploit an embedded network
nodefilebias a value between 0 and 1 (inclusive) that influences operations when "treememlimit" (on how much of the branch-and-bound tree should be kept in memory) has been exceeded: 0 ==> compress every node before writing anything to the "nodefile"; 1 ==> write nodes to the "nodefile" immediately; values between 0 and 1 give intermediate behavior; default = 0.5
nodeselection next MIP node control: 1 = local first: choose among descendant and sibling nodes if available, else from all outstanding nodes 2 = best first of all outstanding nodes 3 = local depth first: choose among descendant and sibling nodes if available, else from deepest nodes 4 = best first for breadthfirst nodes, then local first 5 = pure depth first: choose among deepest nodes. The default is determined from matrix characteristics.
objno objective number (0=none, 1=first...)
objrep Whether to replace minimize obj: v; with minimize obj: f(x) when variable v appears linearly in exactly one constraint of the form s.t. c: v >= f(x); or s.t. c: v == f(x); Possible objrep values: 0 = no 1 = yes for v >= f(x) 2 = yes for v == f(x) (default) 3 = yes in both cases For a maximization problem, "<=" replaces ">=".
optimalitytol tolerance on reduced cost; default = 1e-6
opttol_target feasibility tolerance on reduced costs for solution refiner (see refineops): default = 0; if opttol_target > 0 is specified, it is used instead of optimalitytol.
outlev message level: 1 = all 2 = information 3 = warnings & errors only (default) 4 = errors 5 = none
outputtol zero tolerance on print values; default 1e-5
penalty minimum absolute penalty variable coefficient; default = automatic choice
permuteseed seed for the random-number generator used by prepermute; default = 1
perturb perturb factor if autoperturb is set to 1; 0 = default = automatic choice
pivottol zero tolerance for pivots; default = 1e-9
pooldualred Whether to suppress removal of dominated solutions (via "dual reductions") when poolstub is specified: 0 = yes (default, which can be expensive) 1 = no 2 = honor presolveops bit 3 (2^3 = 8)
pooldupcol Whether to suppress duplicate variable removal when poolstub is specified: 0 = yes (default, which can be expensive) 1 = no 2 = honor presolveops bit 5 (2^5 = 32)
pooldups 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 = default: discard matches of rounded values of discrete variables Rounding of discrete variables is affected by poolmiptol and poolfeastol.
poolfeastol Zero tolerance for discrete variables in the solution pool (see poolstub); default = 1e-6.
poolmiptol Error (nonintegrality) allowed in discrete variables in the solution pool (see poolstub); default = 5e-6.
poolnbest Whether the solution pool (see poolstub) should contain inferior solutions. When poolstub = n > 1, the solution pool is allowed to keep the n best solutions.
poolstub Stub for solution files in the MIP solution pool. Ignored unless some variables are integer or binary. A pool of alternate MIP solutions is computed if poolstub is specified, and the solutions in this pool are written to files (poolstub & '1') ... (poolstub & |solution pool|), where |solution pool| is the number of solutions in the solution pool. That is, file names are obtained by appending 1, 2, ... |solution pool| to poolstub. The value of |solution pool| is returned in suffix npool on the objective and problem.
ppfactor partial-pricing candidate-list size factor; default = 1.0
prebndredcone for MIP problems, whether to use cone constraints to reduce bounds on variables: 0 = no 1 = yes -1 = default (undocumented)
prebndredquad for MIP problems, whether to use convex quadratic constraints to reduce bounds on variables: 0 = no 1 = yes -1 = default (undocumented)
precoefelim whether XPRESSMP's presolve should recombine constraints: 0 = no, 1 = yes, as many as possible 2 = yes, cautiously (default)
precomponents whether XPRESS's presolve should detect and separately solve independent MIP subproblems: -1 = automatic choice (default) 0 = no 1 = yes
predomcol whether XPRESSMP's presolve should remove variables when solving MIP problems: -1 = automatic choice (default) 0 = no 1 = yes, cautiously 2 = yes, check all candidates
predomrow whether XPRESSMP's presolve should remove constraints when solving MIP problems: -1 = automatic choice (default) 0 = no 1 = yes, cautiously 2 = yes, medium strategy 3 = yes, check all candidates
preduprow how XPRESS's presolve should deal with duplicate rows in MIP problems: -1 = automatic choice (default), 0 = do not remove duplicate rows (constraints) 1 = remove duplicate rows identical in all variables 2 = like 1 but allowing simple penalty variables 3 = like 1 but allowing more complex penalty variables
prelindep whether to check for and remove linearly dependent equality constraints: -1 = automatic choice (default) 0 = no 1 = yes
preobjcutdetect on MIP problems, whether to check for constraints that are (nearly) parallel to a linear objective function and can be removed safely: 0 = no 1 = yes (default)
prepermute whether to randomly permute variables or constraints before applying XPRESS's presolve: sum of 1 ==> permute constraints 2 ==> permute variables 4 ==> permute global MIP information default = 0; see permuteseed
preprobing how much probing on binary variables to do during XPRESSMP's presolve: -1 = automatic choice (default) 0 = none 1 = light probing 2 = full probing 3 = repeated full probing
presolve whether to use XPRESS's presolver: 0 = no 1 = yes, removing redundant bounds (default) 2 = yes, retaining redundant bounds
presolvemaxgrow factor by which the number of nonzero coefficients may grow during XPRESS's presolve; default = 0.1
presolveops reductions to use in XPRESSMP's presolve: sum of 1 = 2^0 = remove singleton columns 2 = 2^1 = remove singleton constraints (rows) 4 = 2^2 = forcing row removal (whatever that is) 8 = 2^3 = dual reductions 16 = 2^4 = redundant constraint (row) removal 32 = 2^5 = duplicate variable removal 64 = 2^6 = duplicate constraint removal 128 = 2^7 = strong dual reductions 256 = 2^8 = variable eliminations 512 = 2^9 = no IP reductions 1024 = 2^10 = no semicontinuous variable detection 2048 = 2^11 = no advanced IP reductions 16384 = 2^14 = remove linearly dependent constraints 32768 = 2^15 = no integer variable and SOS detection default = 511 (bits 0-8 set)
pricingalg primal simplex pricing method: -1 = partial pricing 0 = automatic choice (default) 1 = Devex pricing
primal [no assignment] use the primal simplex algorithm
primalunshift whether the primal alg. calls the dual to unshift: 0 = yes (default) 1 = no
pseudocost default pseudo-cost assumed for forcing an integer variable to an integer value; default = 0.01
pseudocost_ud how to update pseudocosts during branch-and-bound: -1 = automatic choice (default) 0 = no updates 1 = use only regular branches 2 = use regular and strong branch results 3 = use results from all nodes
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 means automatic choice.
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 choice (default) 0 = barrier algorithm 1 = dual simplex on outer approximations
quadunshift whether quadratic simplex should do an extra purification after finding a solution: -1 = automatic choice (default) 0 = no 1 = yes
ray whether to return a ray of unboundedness in suffix .unbdd: 0 ==> no (default) 1 ==> yes, after suppressing XPRESS's presolve 2 ==> yes, without suppressing XPRESS's presolve The last setting (ray=2) may give wrong results when XPRESS's presolve detects infeasibility. Both ray=1 and ray=2 cause reoptimization with primal simplex if some other algorithm was used. No ray is returned for MIP problems.
refineops whether refine equalities -- to reduce infeasibilities in constraints that should hold as equalities: sum of 1 ==> refine LP solutions 2 ==> refine MIP solutions; default = 3 (do both)
relax [no assignment] ignore integrality
relaxtreemem fraction of memory limit by which to relax "treememlimit" when too much structural data appears; default 0.1
relpivottol relative pivot tolerance default = 1e-6
repairindefq whether to repair indefinite quadratic forms: 0 = yes 1 = no (default)
rootpresolve whether to presolve after root cutting and heuristics: -1 = automatic choice (default) 0 = no 1 = yes
round whether to round integer variables to integral values before returning the solution, and whether to report that XPRESS returned noninteger values for integer values: sum of 1 ==> round nonintegral integer variables 2 ==> do not modify solve_result 4 ==> do not modify solve_message 8 ==> report modifications even if maxerr < 1e-9 Modifications take place only if XPRESS assigned nonintegral values to one or more integer variables, and (for round < 8) are reported if the maximum deviation from integrality exceeded 1e-9. Default = 1.
sbbest For MIP problems, the number of infeasible global entities on which to perform strong branching; default -1 ==> automatic choice.
sbeffort multiplier on strong-branching controls that are set to "automatic"; default = 1.0
sbestimate how to compute pseudo costs from the local node when selecting an infeasible entity to branch on: -1 = automatic choice (default) 1-6 = particular strategies (not described)
sbiterlimit Number of dual iterations to perform the strong branching; 0 ==> none; default = -1 (automatic choice)
sbselect size of candidate list for strong branching: -2 = low-effort automatic choice (default) -1 = high-effort automatic choice n >= 0 ==> include max(n, sbbest) candidates
scaling how to scale the constraint matrix before optimizing: sum of 1 = 2^0 = row scaling 2 = 2^1 = column scaling 4 = 2^2 = row scaling again 8 = 2^3 = maximum scaling 16 = 2^4 = Curtis-Reid 32 = 2^5 = scale by maximum element (rather than by geometric mean) 128 = 2^7 = objective-function scaling 256 = 2^8 = excluding quadratic part of constraint when calculating scaling factors 512 = 2^9 = scale before presolve 1024 = 2^10 = do not scale constraints (rows) up 2048 = 2^11 = do not scale variables up 4096 = 2^12 = do global objective function scaling 8192 = 2^13 = do right-hand side scaling default = 163
sleeponthreadwait whether threads should sleep while awaiting work: 0 = no (busy-wait) 1 = yes (sleep; may add overhead) default = -1 (automatic choice)
sos whether to use explicit SOS information; default 1 ==> yes
sos2 whether to tell XPRESS about SOS2 constraints for nonconvex piecewise-linear terms; default 1 ==> yes
sosreftol minimum relative gap between reference row entries; default = 1e-6
symmetry amount of effort to detect symmetry in MIP problems: 0 = none: do not attempt symmetry detection 1 = modest effort (default) 2 = aggressive effort
tempbounds whether dual simplex should put temporary bounds on unbounded variables: -1 = automatic choice (default) 0 = no 1 = yes
threads default number of threads to use: -1 = automatic choice (based on hardware) n > 0 ==> use n threads
timing [no assignment] give timing statistics
trace whether to explain infeasibility: 0 = no (default) 1 = yes
treecompress level of effort at data compression when branch-and-bound memory exceeds "treememlimit": higher ==> greater effort (taking more time); default = 2
treecovercuts number of rounds of lifted-cover inequalities at MIP nodes other than the top node (cf covercuts); default = -1 (automatic choice)
treecuts cuts to generate at nodes during tree search: sum of 32 = 2^5 = clique cuts 64 = 2^6 = mixed-integer rounding (MIR) cuts 64 = 2^7 = lifted-cover cuts 2048 = 2^11 = flow-path cuts 4096 = 2^12 = implication cuts 8192 = 2^13 = lift-and-project cuts 16384 = 2^14 = disable cutting from row cuts 32768 = 2^15 = lifted GUB cover cuts 65536 = 2^16 = zero-half cuts 131072 = 2^17 = indicator cuts default = 259839 (same effect as -2305)
treegomcuts number of rounds of Gomory cuts to generate at MIP nodes other than the top node (cf covercuts); default = -1 (automatic choice)
treememlimit an integer: soft limit in megabytes on memory to use for branch-and-bound trees. Default = 0 ==> automatic choice.
treememtarget fraction of "treememlimit" to try to recover by compression or writing to nodefile when "treememlimit" is exceeded. Default = 0.2
treeoutlev how much to report about branch-and-bound trees (if allowed by outlev): sum of 1 = regular summaries 2 = report tree compression and output to nodefile default = 3
treepresolve how much presolving to apply to nodes of the MIP branch-and-bound tree: -1 = automatic choice (default) 0 = none 1 = cautious 2 = moderate 3 = aggressive
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
version Report version details before solving the problem. This is a single-word "phrase" that does not accept a value assignment.
wantsol solution report without -AMPL: sum of 1 = write .sol file 2 = print primal variable values 4 = print dual variable values 8 = do not print solution message