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 -=.
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 archconsistent whether to force the same execution path to be independent of the platform architecture: 0 = no (default) 1 = yes autocutting whether to automatically decide if to generate cutting planes at local nodes (overriden by cutfreq): -1 = automatic (default) 0 = disabled 1 = enabled autoperturb whether to introduce perturbations when the simplex method encounters too many degenerate pivots: 1 = yes (default); 0 = no autoscaling whether the Optimizer should automatically select between different scaling algorithms: -1 = automatic (default) 0 = disabled 1 = cautious strategy. Non-standard scaling will only be selected if it appears to be clearly superior 2 = moderate strategy 3 = aggressive strategy. Standard scaling will only be selected if it appears to be clearly superior backtrack choice of next node when solving MIP problems: -1 = automatic choice (default) 1 = withdrawn; formerly choice 2 until a feasible integer solution has been found, then Forrest-Hirst-Tomlin choice 2 = node with best estimated solution 3 = node with best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 aggressive bardualstop barrier method convergence tolerance on dual infeasibilities; default = 0 (automatic choice) bargapstop barrier method convergence tolerance on the relative duality gap; default = 0 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. barindeflimit maximum indefinite factorizations to allow 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 barkernel how the barrier algorithm weights centrality: >= +1.0 ==> more emphasis on centrality <= -1.0 ==> each iteration, adaptively select a value from [+1, -barkernel]. Default = 1. 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 0 = turn off perturbation n < 0 = force perturbation by abs(n) barobjscale how the barrier algorithm 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) 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 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: -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. 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) 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 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 clamping control adjustements of the returned solution values such that they are always within bounds: -1 ==> determined automatically 0 ==> adjust primal solution to be within primal bounds (default) 1 ==> adjust primal slack values to be within primal bounds 2 ==> adjust dual solution to be within dual bounds 3 ==> adjust reduced costs to be within dual bounds 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: -2 = highest supported [Generic, SSE2, AVX, or AVX2] -1 = highest deterministic support (default; no AVX2) 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 crossoveritlim limit on crossover iterations after the barrier algorithm; default = 2147483645 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 crossoverthreads limit on threads used during crossover; default not specified in the Release 8.2 documentation 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 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) 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) 2 = yes, with opportunistic root LP solve 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) dualperturb Factor by which to possibly perturb the problem in the dual simplex algorithm. If >= 0, overrides "perturb". Default -1 ==> automatic choice; 0 ==> no perturbatation. 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 elimfillin maximum fillins allowed for a presolve elimination; default = 10. 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_perturb how much a feasible primal basic solution is allowed to be perturbed when performing basis changes. The tolerance specified by "feastol" is always considered as an upper limit for the perturbations; default = 1.0E-06 feastol_target feasibility tolerance on constraints for solution refiner (see refineops): if feastol_target > 0 is specified, it is used instead of feastol globalfilemax maximum megabytes for temporary files storing the global search tree: a new file is started if globalfilemax megabytes would be exceeded globalloginterval seconds between additions to the logfile about, additions to the "global file", a temporary file written during a global search. Default = 60. 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. heuremphasis epmphasis for the heuristic search for branch and bound. Setting it to 1 gets a gap quicker at the expense of time to optimality: -1 = default strategy 0 = disable heuristics 1 = focus on reducing the gap early 2 = extremely aggressive heuristics heurforcespecobj whether to use special objective heuristics on large problems and even if an incumbant exists: 0 = no (default) 1 = yes. 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 64 = local search with an auxiliary objective; may be done when no feasible solution is available default = 117 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 deprecated, use heuremphasis: 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 inputtol tolerance on input elements (default 0.0); any value v where abs(v) <= inputtol is treated as 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 lpfolding whether to attempt exploiting symmetries by "LP Folding": -1 = automatic choice (default) 0 = no 1 = yes. 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 maxmemoryhard hard limit (integer number of megabytes) on memory allocated, causing early termination if exceeded 0 (default) = no limit 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 maxstalltime maximum time in seconds that the Optimizer will continue to search for improving solution after finding a new incumbent: 0 ==> no limit (default) n > 0 ==> stop after n seconds without a new incumbent (no effet before the first has been found maxtime limit on solution time: for maxtime=n (an integer), n < 0 ==> stop LP or MIP search after -n seconds n = 0 ==> no time limit (default) n > 0 ==> for MIP problems, stop after n seconds if a feasible solution has been found; otherwise continue until a feasible solution has been found. 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 mipcomponents determines whether disconnected components in a MIP should be solved as separate MIPs: -1 ==> automatic (default) 0 ==> disable 1 ==> enable mipconcurnodes node limit to choose the winning solve when concurrent solves are enabled: -1 ==> automatic (default) n > 0 ==> number of nodes to complete mipconcursolves select the number of concurrent solves to start for a MIP: -1 ==> enabled, the number of concurrent solves depends on mipthreads 0, 1 ==> disabled (default) n > 1 ==> number of concurrent solves = n 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. 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. 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 = allow global tightening of the problem 64 = use objective function 128 = allow restarting 256 = allow use of symmetry default = -1 (automatic choice) 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 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 miprestart MIP: control strategy for in-tree restarts: -1 = determined automatically (default) 0 = disable in-tree restarts 1 = normal aggressiveness 2 = higher aggressiveness miprestartfactor MIP: fine tune initial conditions to trigger an in-tree restart; values > 1 increase the aggressiveness, < 1 decrease it (default 1.0) miprestartgaptol MIP: initial gap threshold to delay in-tree restart; the restart is delayed if the relative gap is below the threshold (default 0.02) 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 netstalllimit limit the number of degenerate pivots of the network simplex algorithmm before switching to primal or dual: -1 ==> automatic 0 ==> no limit n > 0 ==> limit to n iterations network [no assignment] try to find and exploit an embedded network nodefilebias deprecated and ignored: 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 nodeprobingeffort effort put into probing during branch and bound; the number is used as a multiplier on the default amount of work. Set to 0 to disable node probing; default 1. 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 ">=". objscalefactor Power of 2 (default 0) by which the objective is scaled. Nonzero objscalfactor values override automatic global objective scaling. 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 param Used with syntax "param=name=value" (no spaces), where "name" is the name of an XPRESS control parameter and "value" is to be assigned to that parameter. If value is ?, report the current value of the parameter. If name is a string control, value can be a quoted string or a sequence of nonblank characters other than comma. This facility provides a way to modify control parameters, identified by name or number, that have not (yet) been assigned a keyword. As a special case, "param=?" requests a list of all control parameters and their current values. penalty minimum absolute penalty variable coefficient; default = automatic choice permuteseed seed for the random-number generator used by prepermute; default = 1 perturb perturbation factor if autoperturb is set to 1; 0 = default = automatic choice. Deprecated; overridden by primalperturb and dualperturb, which should be used instead of perturb. 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 poolnbest = 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 preanalyticcenter whether to compute and use analytic centers while solving MIP problems: -1 = automatic choice (default) 0 = no 1 = yes, but only for variable fixing 2 = yes, but only for computing reduced costs 3 = yes, for both variable fixing and reduced costs. prebasisred whether XPRESS's presolve should try to use a lattice basis reduction algorithm: -1 = automatic choice (default) 0 = no 1 = yes. 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 XPRESS'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 preconvertsep How to reformulate problems with nondiagonal quadratic objectives or constraints: -1 = automatic choice (default) 0 = no reformulation 1 = reformulate to diagonal constraints 2 = also allow reduction to second-order cones 3 = also convert the objective to a constraint. predomcol whether XPRESS'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 XPRESS'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 prefolding choose if folding aggregate continuous column in an equitable partition: -1 = automatic choiche (default) 0 = disabled 1 = enabled preimplications whether XPRESS's presolve should use implication structures to remove redundant rows: -1 = automatic choice (default) 0 = no 1 = yes 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 XPRESS'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 XPRESS'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). presolvepasses Number of rounds to use in the XPRESS presolve algorithm; default = 1. pricingalg primal simplex pricing method: -1 = partial pricing 0 = automatic choice (default) 1 = Devex pricing primal [no assignment] use the primal simplex algorithm primalperturb Factor by which to possibly perturb the problem in the dual primal algorithm. If >= 0, overrides "perturb". Default -1 ==> automatic choice; 0 ==> no perturbatation. 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; 4 ==> refine the final MIP solution found 8 ==> refine each node of the search tree 16 ==> refine non-global solutions 32 ==> refine all solutions 64 ==> use higher precision during iterative refinement 128 ==> use the primal simplex algorithm for refining 256 ==> use the dual simplex algorithm for refining 512 ==> refine MIP solutions such that rounding them keeps the problem feasible when reoptimized 1024 ==> attempt to refine MIP solutions such that rounding them keeps the problem feasible when reoptimized, but accept integers solutions even if refinement fails. default = 1 + 2 + 16 = 19. 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) resourcestrategy whether to allow nondeterministic decisions to cope with low memory (affected by maxmemory and maxmemoryhard): 0 = no (default) 1 = yes 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) 64 = 2^6 = no special handing for big-M constraints 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 down 4096 = 2^12 = do global objective function scaling 8192 = 2^13 = do right-hand side scaling 16384 = 2^14 = disable aggressive quadratic scaling 32768 = 2^15 = disable explicit slack scaling. Default = 163. 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 siftpasses how quickly we allow the worker problems to grow during the sifting algorithm; large values might reduce the number of iterations but increase the solve time for each. Default 4. siftpresolveops presolve operations for solving the subproblems during sifting: -1 = use presolveops value (default) > 0 = use this value siftswitch determines which algoorithm to use during sifting -1 ==> dual simplex 0 ==> barrier n > 0 ==> barrier if the number of dual infeasibilities > n else dual simplex 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 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 tunerdir directory for tuner results; specifying tunerdir causes the XPRESS tuner to solve the problem several times to find good settings for solving similar problems. Results are stored in tunerdir and its subdirectories. tunerhistory when tunerdir is specified, whether to reuse previous tuner results and/or to augment them: 0 = discard previous tuner results 1 = ignore previous tuner results, but add new results to them 2 = reuse previous tuner results and add new results to them (default). tunermaxtime maximum seconds to run the tuner when tunerdir is specified. Default 0 ==> no limit. Use "maxtime" to limit the time the tuner uses for each problem solved. tunermethod method for tuning when tunerdir 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. tunermethodfile name of a file that can be read to specify the method for tuning (overriding tunermethod) when tunerdir is specified. tunerpermute when running the XPRESS tuner and tunerpermute = n > 0, solve the original problem and n permutations thereof. tunertarget what to measure to compare two problem solutions when running the XPRESS tuner (what to measure): -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 = integrality gap only 8 = best bound only 9 = best integer solution only. tunerthreads number of tuner threads to run in parallel: default -1 ==> automatic choice. "threads" controls the number of threads for each solve. The product of threads and tunerthreads should not exceed the number of threads the system can run in parallel. 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 writeprob Name of file to which the problem is written in a format determined by the name's suffix: .mps = MPS file; .lp = LP file.