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HHuH[]_ fAWAVIAUATIUHSHH<"<'AAHH4H/IT$H=S!HپC1H==! I>Hu fDHHHuHHH[]A\A]A^A_0^AH<bHAHILHHHIIGH)H9v HHHL$HL$HxIHHHL$rIGHL$IF HIGID$I!CEn(IFCIFH[]A\A]A^A_D f.HLJ@AVHcAUAH4@ATUHSHHHHcLXHHL4HLIHADHHCHt-HcKHHH9s@HHHH9Y XwHPIAFI9wDž[]A\A]A^ÐAVHcHcHRIAUATUSH@H`HIH,HË(LPD$0ADAHHHCHt*HcKHHH9sHHHH9Y XwHIAEH9v A(Adž[]A\A]A^@UHSHHHHcS0H1HSHHHHHHuHC( !Xf(HH HHL@HHHAYHXuHBHBHHuHHdH[]DSHHH<$t$ HT$HL$t6HD$x+H4$HD$ HHnH|$fWH$C(<D$ ҉H$HH$@ u19H$H$@ H$t$ HHcƋ 9}6H<$H@HHHHH$HǀH[)HH@HHHfDHt$H<$""DH`H$H1H9Hc$HHHbHfAVLcfWAUIATUSHHD9MHI1ՃItLD$[D$IJ t`|Ht fDHcA Y HIHXuH[]A\A]A^ÐHcA AY Y HIXHuH[]A\A]A^HcQHc Y HIXHuH[]A\A]A^DD( HyHcQHc AY Y HIHXuIAUIATAUSHHHt tLHmbD9H3!}uH[]A\A]DH=a!EL`C1H[]A\A]yWfAUIATIԉUCSHHIHH߉[]LLA\A]Df.ATUSHMH|$t$HT$(HL$LD$ t@HD$ x5H|$HD$0HHdH\$ tH[]A\DHD$H|$HHtHc\$9 (gurobi) %s serverlic file "%s".Bad %s "%s" for %s Missing %s for %s gurobi: Link encap:Ethernet obj_Unrecognized keyword "%s" %s="%s" file nameBad file name "%s" for %s .%s %s("%s") failed: %s. %s=%d link/voidlink/ether inet scope globalCannot openBad assignment invalueCannot open paramfile "%s".Dummy%s failed: %s. %s failed. %s("%s") failed.GRBgetstrparamGRBsetstrparam%s must be %d or %d.%s must be >= %d and <= %d.GRBsetintparamGRBgetintparamGRBgetdblparam%s=%.g GRBsetdblparam%s must be >= %.g and <= %.g.UnbdRayFarkasDualRHSSensedunbdd and %d variables.IISConstrIISLBGRBgetintattrarray("IISLB")IISUBGRBgetintattrarray("IISUB")iis%s; empty IIS!%lunetlicchk: %s line %d of "%s": "%s" Negative integer onExpected an integer onBad port number onMissing IP address onBad IP address on/sbin:/usr/sbin:/binCould not find %s in "%s". Too many args for run()!cmdline too long popen("%s") failure! gurobiLock file corrupted. Corrupted lock file. en_/usr/lib/locale%d-%d-%d-%lxampl.lic$AMPL_LICFILE = "ampl_lic127.0.0.1AMPL_LICFILEPATHBadlbuf overflow on0-0-0-0 Licensed to Bad LOCAL_MGR = %ssocket(...) failedcannot find "%s"not a regular file: "%s"not executable: "%s"Invoking "%s"Could not exec "%s". St %s %lx %lx %s%s%s %sOK No: ampl_lic: %sBad reply from ampl_lic: "%s"%ldLicense file %s: Too much clock skew. Temporary license expired. Maintenance expired %ld. Current directory = "%s". %.*s Computed %s %s wbCould not create "%s" %lu libc.so.6inotify_initinotify_add_watchinotify_rm_watchlicwatch: dlsym() failed. %s (%s, %s), licchk(%ld), ASL(%ld) Bad $gurobi_options.indicator_constrs_ASLGRBaddgenconstrIndicatorfeastol GRBtunemodelReturn %d from %s: %s().GRBgetintattrGRBgettuneresultReturn %d from %s().No tuning results found.GRBwriteparamsinfeasibleinfeasible; no IIS foundinfeasible or unboundedbestbndstop reachedoptimal solutionobjective cutoffsolution limitnumeric errorsuboptimalbestobjstop reachedran out of memorywould be and...s do does< 1 = %g invalid licenseproblem size limit exceededGurobi %d.%d.%dServer = "%s" OutputFlag%s: %sPoolSolutionssstatussosno%s$rangeQCPDualfooGRBloadmodelGRBaddqconstrGRBgetenvGRBaddqptermslazyLazyGRBaddsos%s failed; error code %d.objweight%s is nonlinear. objpriorityobjabstolobjreltolNumObjGRBsetintattr("NumObj")ObjNumberGRBsetintparam("ObjNumber")ObjNGRBsetdblattrelement("ObjN")ObjNConGRBsetdblattr("ObjNCon")ObjNPriorityGRBsetintattr("ObjNPriority")ObjNWeightGRBsetdbkattr("ObjNWeight")ObjNAbsTolGRBsetdbkattr("ObjNAbsTol")ObjNRelTolGRBsetdbkattr("ObjNRelTol")GRBgetmultiobjenv(mdl, %d)"obj_%d_%s %s" rejected. _svar_sconVBasisGRBsetintattrarray("VBasis")CBasisGRBsetintattrarray("CBasis")PStartGRBsetdblattrarray(PStart)DStartGRBsetdblattrarray(DStart)VarHintValGRBsetdblattrarray(Varhint)hintpriVarHintPriGRBsetdblattrarray(Hintpri)GRBsetdblattrarray(START)LogFileGRBwriteInfUnbdInfoBranchPrioritylbpenrhspenubpenGRBfeasrelaxTuneResultCount%d%sStatusGRBgetintattr(STATUS)%s; variable.unbdd returned.SolCountObjValBestBdStopBestObjStopQCPi; %sobjective %.*g feasrelax objective = %.*gObjBoundrelmipgapabsmipgapbestboundBarIterCount %d barrier iterations %.0f simplex iterationsNodeCount %.0f branch-and-cut nodesPresolvesetintparam("Presolve")optimize()getintattr()GRBgetdblattrarray No basis.Surprise VBasis[%d] = %d.Surprise CBasis[%d] = %d. No %s variables returned.SolutionNumberXn%d.sol %s %s "%s%d.sol".0.solGRB_LICENSE_FILEgurobiserver--helpgurobiserver_optionsnon0000000000000001234567890003FF00056900059A3C78000C29000D3A000F4B00125A00155D00155EBAC000163E0017FA001C14001C42001DD80050560050F2005345000000020054554E010215E0EC01000250F20000028037EC02000800270A00274445535400004445535442005455434452LC_ALLLC_MESSAGESLANGifconfigaddrshowhostnameADDRANGEIGNORE_CLIENT_FPIPRANGELIC_HOLDLIC_MGRLOCAL_IPLOGFILEMGR_IPMGR_RETRY_INCMGR_RETRY_MAXMGR_RETRY_MINPING_WAITPORTPROC_CHKQUIET_WAITSAVE_WAITSTATEFILEVERBOSEVERBOSE_WAITprimalprimal or dualsenslbhiSALBUpsenslbloSALBLowsensobjhiSAObjUpsensobjloSAObjLowsensrhshiSARHSUpsensrhsloSARHSLowsensubhiSAUBUpsensubloSAUBLowiteration limitnode limittime limitinterruptednumeric difficultycomputeserversynonym for "server"synonym for "server_password"server_passwordserver_portserver_priorityserver_timeoutbasfix_lpfix_mpsprmrewrlpsosrefgurobi_optionsaggfillAggFillaggregateAggregateams_epsams_epsabsPoolSearchModeams_stubbarconvtolBarConvTolbarcorrectorsBarCorrectorsbarhomogeneousBarHomogeneousbariterlimBarIterLimitbarorderBarOrderbarqcptolBarQCPConvTolbasisdebugbestbndstopbestobjstopbranchdirBranchDircliquecutsCliqueCutscloudidcloudkeycloudpoolconcurrentmipConcurrentMIPcovercutscrossoverCrossovercrossoverbasisCrossoverBasiscutaggCutAggPassesCutoffcutpassesCutPassesdegenmovesDegenMovesdisconnectedDisconnecteddualreductionsDualReductionsfeasrelaxbigmFeasRelaxBigMFeasibilityTolflowcoverFlowCoverCutsflowpathFlowPathCutsgomoryGomoryPassesgubcoverGUBCoverCutsheurfracHeuristicsiisfindiismethodIISMethodimpliedImpliedCutsimprovegapImproveStartGapimprovetimeImproveStartTimeimpstartnodesImproveStartNodesinfproofcutsInfProofCutsintfeastolIntFeasTolintstartIterationLimitSee feasrelax.logfilelogfreqDisplayIntervallpmethodsynonym for "method"maxmipsubSubMIPNodesminrelnodesMinRelNodesmipfocusMIPFocusMipGapmipgapabsMipGapAbsmipsepMIPSepCutsmipstartmiqcpmethodMIQCPMethodmircutsMIRCutsmodkcutsModKCutsmultiobjmultiobjmethodMultiObjMethodmultiobjpreMultiObjPremultprice_normNormAdjustnetworkcutsNetworkCutsnodefiledirNodefileDirnodefilestartNodefileStartnodelimnodemethodNodeMethodnormadjustsynonym for "multprice_norm"numericfocusNumericFocusobjnoobjrepobjscaleObjScaleopttolOptimalityToloutlevparamfileperturbPerturbValuepivtolMarkowitzTolpl_bigmpool_distmipDistributedMIPJobspool_mipConcurrentJobspool_passwordWorkerPasswordpool_serversWorkerPoolpool_tunejobsTuneJobspoolsearchmodesynonym for ams_modepoolsolutionssynonym for ams_limitpredeprowPreDepRowpredualPreDualpremiqcpformPreMIQCPFormprepasesPrePassesprepassespreqlinearizePreQLinearizepresolvepresos1bigmPreSOS1BigMpresos2bigmPreSOS2BigMpresparsifyPreSparsifypricingSimplexPricingprioritiespsdtolPSDTolpumppassesPumpPassesqcpdualquadQuadraysresultfileResultFilereturn_mipgaprinsRINSroundround_reptolScaleFlagSeedserverlicsiftingSiftingsiftmethodSiftMethodsimplexsynonym for "lpmethod"solnlimitSolutionLimitsolnsenssos2startnodelimitStartNodeLimitsubmipcutsSubMIPCutssubmipnodessymmetrySymmetrythreadsThreadstimelimtimingtunebasetuneoutputTuneOutputtuneresultsTuneResultstunetimelimitTuneTimeLimittunetrialsTuneTrialsvarbranchVarBranchwantsolwarmstartwriteprobzerohalfcutsZeroHalfCutszeroobjnodesZeroObjNodesTemporary license expires gurobi driver: %d messages about bad %s.sstatus values suppressed. Rejecting obj_%d; obj_n must have 1 <= n <= %d File name for %s must end in one of Expected an integer value for %s, not "%s" rejecting %s %d; must be between %d and %d Expected a numeric value for %s, not "%s" GRBgetintattrarray("IISConstr")%s Returning an IIS of %d constraints%s Returning an IIS of %d variables.Lock file "%s" exists but is wrongly formatted. License "%s" for gurobi (invoked as %s) is busy with pid %lu. License "%s" for gurobi is busy with pid %lu. lic_init: inotify_init() failed. lic_init: inotify_add_watch failed. Unexpected return from select. connection refused. Is ampl_lic running on the network license server?unreachable network/no route to host. Are the client and network license server on the same network? Can you ping the network license server from the client?connection timed out. Is port %d blocked on the client or network license server?Demo license with maintenance expiring $AMPL_LICFILE is too long: "%.*s" Cannot open $AMPL_LICFILE = "%s" License file %s%s%s not found anywhere in $PATH. User id check: expected %ld, got %ldTrying to start license manager ampl_licDirectory name too long for "%s"not executable by user %u: "%s"not executable by group %u: "%s"Could not connect with license manager: errno %d: %sbuf too small: bname = "%s" sname = "%s"socket write returned %d rather than %dmalloc(%ld) failure in netlicchkToday = %lu; found license file "%s": No gurobi license for this machine. licwatch: dlopen("libc.so.6") failed. lic_init: failed to create licwatch thread Could not create the gurobi environment.Job rejected by Gurobi Compute Server.Job rejected by Gurobi Instant Cloud.Could not talk to Gurobi Compute Server.No license for specified Gurobi Compute Server.Could not talk to Gurobi Instant Cloud.Bad value for cloudid or cloudkey, or Gurobi Cloud out of reach.No license for specified Gurobi Instant Cloud.No tuning results available: return %d from %s(): %s.No tuning results available: return %d from %s().interation limit without a feasible solutioniteration limit with a feasible solutionnode limit without a feasible solutionnode limit with a feasible solutiontime limit without a feasible solutiontime limit with a feasible solutioninterrupted without a feasible solutioninterrupted with a feasible solutionbestobjstop or bestbndstop reachedinfeasible or unbounded; no IISbestobjstop or bestbndstop reached with no solution availablesolution found but not available (Gurobi bug?)quadratic objective or constraint is not positive definitequadratic objective is not positive definitebug: IIS problem is infeasibleGurobi Compute Server not reachedRejected by Gurobi Compute Server -- perhaps the queue was too full or queueing time was exceeded.Feature not supported by Gurobi Compute Serverquadratic constraint is not positive definitePortions Copyright Gurobi Optimization, Inc., 2008.Gurobi can't handle complementarity constraints.Could not talk to Gurobi Compute Server "%s" Job rejected by Gurobi Compute Server "%s" Surprise return %d from GRBloadclientenv(). Surprise return %d from GRBloadclientenv().Surprise return %d from GRBloadcloudenv().Cannot handle a quadratic objective involving division by 0Gurobi cannot handle general nonlinear objectives.The problem has %d free row%s, which gurobi cannot handle. You need to let AMPL's presolve remove free rows. no quadratic terms in a "quadratic" constraint.a quadratic constraint involving division by 0.Gurobi can't handle nonquadratic nonlinear constraints.Gurobi cannot handle quadratic equality constraints.Gurobi cannot handle quadratic range constraints.Surprise return %d from GRBsetintattrelement(mdl, "Lazy", %d, %d) logical constraint %s is not an indicator constraint. logical constraint %s is not an indicator constraint due to bad comparison with %s. %s.objweight = %.g is negative. Expected at least 2 positive .objweight values; found %d. Expected a positive weight for objective objno = %d. %s.objpriority = %d should be nonnegative. %s.objabstol = %.g should be nonnegative. %s.objreltol = %.g should be nonnegative. GRBsetintattrarray("BranchPriority")Surprise return %d from %s() after writing %d %.*s*%s files.Wrote tuning parameter file "%s".Wrote tuning parameter files "%s" and "%.*s2%s".Wrote %d tuning parameter files "%s" ... "%.*s%d%s".surprise return %d from GRBoptimize%s; constraint.dunbdd returned.surprise status %d after GRBoptimize GRBgetenv failed in fixed_model(). intbasis trouble: GRB%s failed. GRBoptimize of fixed model: %s. Surprise status %d after GRBoptimize of fixed model. plus %.0f simplex iteration%s for intbasis absmipgap = %.3g, relmipgap = %.3gAlternative MIP solution %d, objective = %.*g %d integer variables %srounded to integers; maxerr = %g Ignoring %d other inferior alternative MIP solutions. Alternative solution%s not include dual variable values. Best solution is available in "%s0.sol". %d integer variable%s %srounded to integer%s; maxerr = %g Times (seconds): Input = %g Solve = %g (summed over threads) Output = %g Elapsed %d alternative MIP solution%s written to "%s1.sol"%s Usage: %s [options] stub [-AMPL] [ ...] to use a remote Gurobi server rather than running gurobi locally. $gurobiserver_options (i.e., AMPL option gurobiserver_options) must provide at least a "server = ..." assignment to specify the server. It may contain other "server_..." assignments described in the output of "gurobi -=" or "gurobi '-='". Invoke "gurobi -h" to see a summary of other command-line options. $gurobiserver_options not set Bad value in $gurobiserver_options: "%s" $gurobiserver_options has server_priority = %d. Expected 1 <= server_priority <= 100. No "server=..." found in serverlic file "%s". No "server=..." found in $gurobiserver_options. Sorry, a demo license is limited to %d variables and %d constraints and objectives for %slinear problems. You have %d variables, %d constraints, and %d objective%s. flowcover cuts: overrides "cuts"; choices as for "cuts"flowpath cuts: overrides "cuts"; choices as for "cuts"gubcover cuts: overrides "cuts"; choices as for "cuts"implied cuts: overrides "cuts"; choices as for "cuts"iteration limit (default: no limit)max. relative MIP optimality gap (default 1e-4)absolute MIP optimality gap (default 1e-10)MIPsep cuts: overrides "cuts"; choices as for "cuts"MIR cuts: overrides "cuts"; choices as for "cuts"mod-k cuts: overrides "cuts"; choices as for "cuts"Network cuts: overrides "cuts"; choices as for "cuts"maximum MIP nodes to explore (default: no limit)Markowitz pivot tolerance (default 7.8125e-3)deprecated synonym for "prepasses"maximum MIP solutions to find (default 2e9)sub-MIP cuts: overrides "cuts"; choices as for "cuts"limit on solve time (in seconds; default: no limit)zero-half cuts: overrides "cuts"; choices as for "cuts"Maintenance expires with version @@@@@@@@@i@@@@@p@@@@@[@@=@G@Q@@@9@p@@@]@w@@@@@@@Z@@t@alic_lock.RCRCRC0 ,aQ mj5cd2+L|-d HqA} QDžVlk zbeO\lc=  n^iA`rqgG k l ɻ@lu\ Y=0:Qa#ij $ |oLha=-fAq * 3Ը4  j-=mld\cQk bal0eNb{WٰP긾| I-|eLXa Qt0AוmjinFgи`s- _L | jmZj  'Dңh ]Wbgeq6lkv+ZzJo߹CՎ ~R ggWK6+ L J`z`Ugnyi afo6hw G /&;( Zj1d&cj m ?6gWJz+8 !Bn[&w wGZpj; \ eibkElx T³a&g`MGi wnJjZf ;SŞϲº06)Wg.zfJah+o7  SCSCSCJCJCJC6KCtTCTCTC=KCTCTCZKC<>=|C[_C0123456789ABCDEF. Using license file "}Ô%IT??\nT|=ư>ABCDEFGHIJKLMNOPQRSTUVWXYZ malloc failure in dtoa! nfInfinityNaNXA A A A A A A A AAAAAA A A A A A A A A A A A A A A A A A AA A A A A A A A A A AA AA}ؗҜ<3#I9=D2[%Cod(h7yACnF?O8M20HwZ>>????@@@AAABBBBCCCDDDEEEEFFFGGGHHHHIIIJJJKKKKLLLMMMNNNNOOOPPPQQQRRRRSSSTTTUUUUVVVWWWXXXXYYYZZZ[[[[\\\]]]^^^^___```aaaabbbcccddddeeefffgggghhhiiijjjjkkklllmmmnnnnooopppqqqqrrrsssttttuuuvvvwwwwxxxyyyzzzz{{{|||}}}}~~~                    !!!""""###$$$%%%%&&&'''(((()))***++++,,,---....///000111122233344445556667777888999:::;;;;<<<===>>>>???@@@AAAABBBCCCDDDDEEEFFFGGGGHHHIIIJJJJKKKLLLMMMMNNNOOOPPPPQQQRRRSSSSTTTUUUVVVVWWWXXXYYYZZZZ[[[\\\]]]]^^^___````aaabbbccccdddeeeffffggghhhiiiijjjkkkllllmmmnnnoooopppqqqrrrrssstttuuuvvvvwwwxxxyyyyzzz{{{||||}}}~~~                    !!!"""###$$$$%%%&&&''''((()))****+++,,,----...///0000111222333344455566667778889999:::;;;<<<<===>>>????@@@AAABBBCCCCDDDEEEFFFFGGGHHHIIIIJJJKKKLLLLMMMNNNOOOOPPPQQQRRRRSSSTTTUUUUVVVWWWXXXXYYYZZZ[[[[\\\]]]^^^____```aaabbbbcccdddeeeefffggghhhhiiijjjkkkklllmmmnnnnooopppqqqqrrrsssttttuuuvvvwwwwxxxyyyzzzz{{{|||}}}~~~~@A5?55?5?P9-i options: %s Options: -%-*s{%s} -%s%-*.*s{%s} -%s Bad value in "%.*s" Unknown keyword "%.*s" ???%s%.*s%s (%s), driver(%ld)getopts'%c''\x%x' %s%s%.*s %*s Bad character * in numeric string "%.*s". getstubsolver_msg%s%-*.*s%s %-*s%s %-*s%.*s %s: bad option %s -AMPLgetstopsNo stub! -end of options=show name= possibilitiesshow usagebfread boundsfile fixofwrite .sol file to file fjust show versionusage: %s [options] stub [-AMPL] [ ...] suppress echoing of assignmentsimport user-defined functions from x; -i? gives detailswrite .sol file (without -AMPL)just show available user-defined functionszeAeAeAeAeAeAeAeAeAeAeAeAeAeAeAeAhdAeAieAeAeAeAeAeAeAeAeAeAeAeAeAeAeAeAeAeAeAeAeAeAeAeAeAeAeAeAeAeAeAeAeAeAeAhAeAeA@fAeAeAeAxhAeAeAeAeAeAeAeAeAeAgAeA@hAhA mA0mA@mAhlAhlAhlAplAlAmAxAyAxAxAyAyAyAvAyAyAyAyAyAyAyAyAyAyAyAyAyAyAyAyAyAyAyAyAyAyAyAyAyAyAyAyAyAyAyAyAyAyAyAyAyAyAyAyAyAwA~A~A}A}A;}AAgot only %d integers; wanted %d ampl_options = %d is too large jacdim: got M = %d, N = %d, NO = %d %hdjac0dim.nlcan't open %s %d %d %d %d %d %dUnrecognized binary format. %D %DA(A(A(A(AAxA(A(A(A(A(A(A(A(A(A(A(A(A(A(A(A(A(APA(A(A(A(A(A(A(AA(A(A(A(AAxA(A(A(A(A(A(A(A(A(A(A(A(A(A(A(A(A(APA *** %s called before %s. pfgh_read or jacpdimsputsetfullhesduthesxknownconivalduthes, fullhes, or sputhespfgh_readhvinitpfgh_read or fgh_readhvcompshvcompdhvcompcongrdjacvalconvalobjgrdobjval %s: %s(%lu) failure: %s. bad line %ld of %s: %s %s called after ASL_alloc(). xunknoCannot open boundsfile "%s".Bounds, x; arith Bad magic in boundsfile "%s".suf_declaresuf_getsuf_get("%s") fails! Premature end of file, line %ld of %s error reading line %ld of %s: *** %s needs ASL_alloc(%d), not ASL_alloc(%d) *** %s called before ASL_alloc(%d) *** %s called before ASL_alloc, jacdim, jac2dim, or jacpdim %s: got M = %ld, N = %ld, NZ = %ld expected M = %d, N = %d, NZ = %d BUG: %s called with want_derivs == 0. *** Problem too large (%.g Jacobian nonzeros) *** Problem too large (%.g Jacobian nonzeros) for jacval(). Recompile ASL with "#define ASL_big_goff" added to arith.h. Expected %d bounds triples in boundsfile "%s"; got %d.%d too few bound triples in boundsfile "%s".bad bound triple %d in bounds file "%s": L = %.g x = %.g U = %.gBound triple %d: bad number "%.*s" in boundsfile "%s".@AxAxAhA AAA ERROR: mpec_adjust saw %d rather than %d incoming complementarities. AAAA AMAPAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAA8AAAAAAnqpcheck.row_scon[%d]_scon_aux[%d]_slogcon[%d]_sobj[%d]_svar_aux.col%s[%d]Bug: surprise ASLtype = %d in obj_adj objective_precisionXBBBBBBBBBBBXBBB(BB`BmBmBmBmBmBmBmBmBmBBBBBBBBBBBB@BBBBBBBBBBBBBBBBBBBpBBBBBBBBBBB B`B@BBBpB`BBBBBBBBBBBBBBBhBBB BUG! Sput called! qp_opify: bad op field qp_opifyedqpreaded1opwalk bug! optype[%d] = %d x5B4B4B5B4BP5B`4B4B4B4B4B4Bpowpow' div /atanhlogacosacos'acoshacosh'asinhsqrtsqrt'asinasin'atanatan2sinh'explog10tan'tanh'fmode%d &{?$@bad fmt in Sscanf, starting with "%s" /BBBB~BG~B%s%s%s %s%s%ld %s%s%d %-*s%.g %s%*s%svalue write_solersion binaryOptionsOptions %ld %ld %ld %ld objno %d objno %d %d %d %.g variabledual constraintsuffix %ld %ld %ld %ld %ld %s NUCbICbad format %s %lf %lfsymbolic fg_readlogical constraintsSorry, %s cannot handle %s. %d %d %d %127sfunction %s not available %d %d %lf BBBB@BPB@BB8BBBBPBBBBBBBXBBBBBBBPBBhB{BBBBBxBBBB BBBBB]B BBBBBBByBBBBBBBBBBBBBBBpBBBBBBBBB]BBBBBBB`BBBBBBB?&@&@&@&@&@&@???Attempt to call unavailable function %s.Premature end of file in aholread, line %ld of %s line %ld: attempt to call %s with %d %sargs edagread: nc = %d, no = %d, nlcon = %d function %s: disagreement of nargs: %d and %d &@randseed/tmpTMPDIRTemp_ampl_funclibsAMPLFUNCat least real %s(%s%d %sarg%s) noneaddfunc: duplicate function %s function %s: ftype = %d; expected 0 or 1 Available nonstandard functions:%s : %s Cannot load library "%s"funcadd_ASLfuncaddCould not find funcadd in %s Cannot find library "%s". Cannot find library "%.*s". ? {show -i options}by single or double quotes.- {do not import functions: do not access amplfunc.dll}dir {look for amplfunc.dll in directory dir}file {import functions from file rather than amplfunc.dll}When the x of -ix is suitably quoted, multiple files may appear onseparate lines or may appear on the same line if each is enclosedIf no -i option appears but $ampl_funclibs is set, assume-i $ampl_funclibs. Otherwise, if $AMPLFUNC is set, assume-i $AMPLFUNC. Otherwise look for amplfunc.dll in thedirectory that is current when execution begins.-ix and -i x are treated alike.CCobjval: got NOBJ = %d; expected 0 <= NOBJ < %d x1knownobj1valError evaluating var %s: "var =" definition %d: %s can't compute %g%s0. function: objectiveError in function %s: %s can't evaluate %s(%g,%g). can't evaluate %s(%g). 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Default = 0.Whether to use incoming primal and dual variable values (if both are available) in a simplex warm start: 0 = no; 1 = yes if there is no incoming basis (default); 2 = yes, ignoring the incoming basis (if any); 3 = no, but on MIP problems, use the incoming primal values as hints, ignoring the .hintpri suffix; 4 = similar to 3, but use the .hintpri suffix on variables: larger (integer) values give greater priority to the initial value of the associated variable. Note that specifying basis=0 or basis=2 causes there to be no incoming basis. This is relevant to warmstart values 1, 3, and 4. For continuous problems, warmstart values >= 2 are treated as 1.MIP symmetry detection: -1 = automatic choice (default) 0 = none 1 = conservative 2 = agressivehow often to apply the RINS heuristic for MIP problems: -1 = automatic choice (default) 0 = never n > 0: every n-th nodename of a file of extra information written after completion of optimization. The name's suffix determines what is written: .sol solution vector .bas simplex basis .mst integer variable solution vectorwhether simplex should use quad-precision: -1 = automatic choice (default) 0 = no 1 = yesWhether Gurobi's presolve should use its "sparsify reduction", which sometimes gives significant problem-size reductions: 0 = no (default) 1 = yes.How Gurobi's presolve should treat quadratic problems: -1 = automatic choice (default) 0 = do not modify the quadratic part(s) 1 = try to linearize quadratic partslimit on the number of Gurobi presolve passes: -1 = automatic choice (automatic) n >= 0: at most n passesgigabytes of memory to use for MIP tree nodes; default = Infinity (no limit, i.e., no node files written)directory where MIP tree nodes are written after memory for them exceeds nodefilestart; default "."choice of norm used in multiple pricing: -1 = automatic choice (default) 0, 1, 2, 3 = specific choices: hard to describe, but sometimes a specific choice will perform much better than the automatic choice.=... 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 messagename of a GUROBI-format file to be written (for debugging); must end in one of ".bas", ".lp", ".mps", ".prm", ".rew", ".rlp", ".sol", or for the "fixed" model used to recover a basis or dual values for problems with integer variables or quadratic constraints, ".fix_lp" or ".fix_mps"; the '_' will be replaced by '.' in the name of the file written for ".fix_lp" or ".fix_mps". Can appear more than once with different filenames.Report version details before solving the problem. This is a single-word "phrase" that does not accept a value assignment.MIP branch variable selection strategy: -1 = automatic choice (default) 0 = pseudo reduced-cost branching 1 = pseudo shadow-price branching 2 = maximum infeasibility branching 3 = strong branchingnumber of trials for each parameter set when tunebase is specified, each with a different random seed value. Default = 2.time limit (in seconds) on tuning when tunebase is specified. Default -1 ==> automatic choice of time limit.limit on the number of tuning result files to write when tunerbase is specified. The default (-1) is to write results for all parameter sets on the efficient frontier.amount of tuning output when tunebase is specified: 0 = none 1 = summarize each new best parameter set 2 = summarize each set tried (default) 3 = summary plus detailed solver output for each trialbase name for results of running Gurobi's search for better parameter settings. The search is run only when tunebase is specified. Results are written to files with names derived from tunebase by appending ".prm" if ".prm" does not occur in tunebase and inserting 1, 2, ... (for the first, second, ... set of parameter settings) before the right-most ".prm". The file with "1" inserted is the best set and the solve results returned are for this set. In a subsequent "solve;", you can use paramfile=... to apply the settings in results file ... .whether to report timing: 0 (default) = no 1 = report times on stdout 2 = report times on stderrhow many threads to use when using the barrier algorithm or solving MIP problems; default 0 ==> automatic choice.limit on nodes explored by MIP-based heuristics, e.g., RINS. Default = 500.limit on how many branch-and-bound nodes to explore when doing a partial MIP start: -2 = suppress MIP start processing -1 = use submipnodes (default) >= 0 ==> specific node limitwhether to tell Gurobi about SOS2 constraints for nonconvex piecewise-linear terms: 0 = no 1 = yes (default), using suffixes .sos and .sosref provided by AMPL.whether to honor declared suffixes .sosno and .ref describing SOS sets: 0 = no 1 = yes (default): 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.whether to return suffixes for solution sensitivities, i.e., ranges of values for which the optimal basis remains optimal: 0 = no (default) 1 = yes: suffixes return on variables are .sensobjlo = smallest objective coefficient .sensobjhi = greatest objective coefficient .senslblo = smallest variable lower bound .senslbhi = greatest variable lower bound .sensublo = smallest variable upper bound .sensubhi = greatest variable upper bound suffixes for constraints are .sensrhslo = smallest right-hand side value .sensrhshi = greatest right-hand side value For problems with integer variables and quadratic constraints, solnsens = 0 is assumed quietly.which algorithm to use for non-MIP problems or for the root node of MIP problems: -1 automatic (default): 3 for LP, 2 for QP, 1 for MIP root node 0 = primal simplex 1 = dual simplex (default) 2 = barrier 3 = nondeterministic concurrent (several solves in parallel) 4 = deterministic concurrentwhether to scale the problem: 0 = no 1 = yes (default) 2 = yes, more aggressively.Algorithm to use for sifting with the dual simplex method: -1 = automatic choice (default) 0 = primal simplex 1 = dual simplex 2 = barrier.whether to use sifting within the dual simplex algorithm, which can be useful when there are many more variables than constraints: -1 = automatic choice (default) 0 = no 1 = yes, moderate sifting 2 = yes, aggressive sifting.random number seed (default 0), affecting perturbations that may influence the solution path.Tolerance for reporting rounding of integer variables to integer values; see "round". Default = 1e-9.Whether to round integer variables to integral values before returning the solution, and whether to report that GUROBI returned noninteger values for integer values: sum of 1 ==> round nonintegral integer variables 2 ==> modify solve_result 4 ==> modify solve_message Default = 7. Modifications that were or would be made are reported in solve_result and solve_message only if the maximum deviation from integrality exceeded round_reptol.Whether to return mipgap suffixes or include mipgap values (|objectve - best_bound|) 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.whether to relax integrality: 0 = no (default) 1 = yes: treat integer and binary variables as continuousWhether to return suffix .unbdd if the objective is unbounded or suffix .dunbdd if the constraints are infeasible: 0 = neither 1 = just .unbdd 2 = just .dunbdd 3 = both (default)Whether to compute dual variables when the problem has quadratic constraints (which can be expensive): 0 = no (default) 1 = yesnumber of feasibility-pump passes to do after the MIP root when no other root heuristoc found a feasible solution (default 0)maximum diagonal perturbation to correct indefiniteness in quadratic objectives (default 1e-6)Whether to use the variable.priority suffix with MIP problems. When several branching candidates are available, a variable with the highest .priority is chosen for the next branch. Priorities are nonnegative integers (default 0). Possible values for "priorities": 0 = ignore .priority; assume priority 0 for all vars 1 = use .priority if present (default).pricing strategy: -1 = automatic choice (default) 0 = partial pricing 1 = steepest edge 2 = Devex 3 = quick-start steepest edgewhether to use Gurobi's presolve: -1 (default) = automatic choice 0 = no 1 = conservative presolve 2 = aggressive presolvenumber of parallel tuning jobs (default 0) to run on the server (if specified by pool_servers). Tuning results are not normalized by server performance, so tuning is most effective when all the servers in the server pool have similar performance characteristics.comma-separated list of server names or IP addresses of machines in the server pool (default "" = none)password for the server pool (if needed)number of independent MIP jobs (default 0) to generate and solve using the server pool (if specified by pool_servers). Gurobi automatically chooses different algorithm parameter values for each job.number of machines in the server pool (if specified by pool_servers) to use for solving each MIP instance.Big-M for converting SOS2 constraints to binary form: -1 = automatic choice 0 = no conversion (default) Large values (e.g., 1e8) may cause numeric trouble.Big-M for converting SOS1 constraints to binary form: -1 = automatic choice (default) 0 = no conversion Large values (e.g., 1e8) may cause numeric trouble.For mixed-integer quadratically constrained (MIQCP) problems, how Gurobi should transform quadratic constraints: -1 = automatic choice (default) 0 = retain MIQCP form 1 = transform to second-order cone contraints 2 = transform to rotated cone constraints Choices 0 and 1 work with general quadratic constraints. Choices 1 and 2 only work with constraints of suitable forms.whether gurobi's presolve should form the dual of a continuous model: -1 = automatic choice (default) 0 = no 1 = yes 2 = form both primal and dual and use two threads to choose heuristically between themwhether Gurobi's presolve should remove linearly dependent constraint-matrix rows: -1 = only for continuous models 0 = never 1 = for all modelsname of file (surrounded by 'single' or "double" quotes if the name contains blanks) of parameter names and values for them. Lines that start with # are ignored. Otherwise, each nonempty line should contain a name and a value, separated by a space.general way to specify values of both documented and undocumented Gurobi parameters; value should be a quoted string (delimited by ' or ") containing a parameter name, a space, and the value to be assigned to the parameter. Can appear more than once. Cannot be used to query current parameter values.magnitude of simplex perturbation (when needed; default 2e-4)overrides "cuts"; choices as for "cuts"whether to write Gurobi log lines (chatter) to stdout: 0 = no (default) 1 = yes (see logfreq)optimality tolerance on reduced costs (default 1e-6)how to scale the objective: 0 ==> automatic choice (default) negative >= -1 ==> divide by max abs. coefficient raised to this power positive ==> divide by this valueWhether 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 maximization problems, ">= f(x)" is changed to "<= f(x)" in the description above.objective to optimize: 0 = none 1 = first (default, if available), 2 = second (if available), etc.how much to try detecting and managing numerical issues: 0 = automatic choice (default) 1-3 = increasing focus on more stable computationsalgorithm used to solve relaxed MIP node problems: 0 = primal simplex 1 = dual simplex (default) 2 = barrierhow to apply Gurobi's presolve when doing multi-objective optimization: -1 = automatic choice (default) 0 = do not use Gurobi's presolve 1 = conservative presolve 2 = aggressive presolve, which may degrade lower- priority objectives.choice of optimization algorithm for lower-priority objectives: -1 = automatic choice (default) 0 = primal simplex 1 = dual simplex 2 = ignore warm-start information; use the algorithm specified by the method keyword. The method keyword determines the algorithm to use for the highest priority objective.whether to do multi-objective optimization: 0 = no (default) 1 = yes When multiobj = 1 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. 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. The objective indicated by objno can be general; all others must be linear. Objective-specific convergence tolerances and method values may be assigned via keywords of the form obj_n_name, such as obj_1_method for the first objective.Method for solving mixed-integer quadratically constrained (MIQCP) problems: -1 = automatic choice (default) 0 = solve continuous QCP relaxations at each node 1 = use linearized outer approximationswhether to use initial guesses in problems with integer variables: 0 = no 1 = yes (default)MIP solution strategy: 0 = balance finding good feasible solutions and proving optimality (default) 1 = favor finding feasible solutions 2 = favor proving optimality 3 = focus on improving the best objective boundnumber of nodes for the Minimum Relaxation heuristic to explore at the MIP root node when a feasible solution has not been found by any other heuristic (default 0)maximum number of nodes for RIMS heuristic to explore on MIP problems (default 500)interval in seconds between log lines (default 5)name of file to receive log lines (default: none); implies outlev = 1whether to honor suffix .lazy on linear constraints in problems with binary or integer variables: 0 = no (ignore .lazy) 1 = yes (default) Lazy constraints are indicated with .lazy values of 1, 2, or 3 and are ignored until a solution feasible to the remaining constraints is found. What happens next depends on the values of .lazy: 1 ==> the constraint may still be ignored if another lazy constraint cuts off the current solution; 2 ==> the constraint will henceforth be enforced if it is violated by the current solution; 3 ==> the constraint will henceforth be enforced.when there are integer variables, whether to use an initial guess (if available): 0 = no 1 = yes (default)feasibility tolerance for integer variables (default 1e-05)execution seconds after which the MIP solver switches from trying to improve the best bound to trying to find better feasible solutions (default Infinity)number of MIP nodes after which the solution strategy will change from improving the best bound to finding better feasible solutions (default 0)optimality gap below which the MIP solver switches from trying to improve the best bound to trying to find better feasible solutions (default 0)whether to generate infeasibility proof cuts: -1 = automatic choice (default) 0 = no 1 = moderate cut generation 2 = aggressive cut generationwhich method to use when finding an IIS (irreducible infeasible set of constraints, including variable bounds): -1 = automatic choice (default) 0 = often faster than method 1 1 = can find a smaller IIS than method 0whether to return an IIS (via suffix .iis) when the problem is infeasible: 0 = no (default) 1 ==> yesfraction of time to spend in MIP heuristics (default 0.05)maximum number of Gomory cut passes during cut generation (-1 = default = no limit); overrides "cuts"primal feasibility tolerance (default 1e-6)Value of "big-M" sometimes used with constraints when doing a feasibility relaxation. Default = 1e6.Whether to modify the problem into a feasibility relaxation problem: 0 = no (default) 1 = yes, minimizing the weighted sum of violations 2 = yes, minimizing the weighted count of violations 3 = yes, minimizing the sum of squared violations 4-6 = same objective as 1-3, but also optimize the original objective, subject to the violation objective being minimized Weights are given by suffixes .lbpen and .ubpen on variables and .rhspen on constraints (when positive), else by keywords lbpen, ubpen, and rhspen, respectively (default values = 1). Weights <= 0 are treated as Infinity, allowing no violation.global cut generation control, valid unless overridden by individual cut-type controls: -1 = automatic choice (default) 0 = no cuts 1 = conservative cut generation 2 = aggressive cut generation 3 = very aggressive cut generationwhether Gurobi's presolve should use dual reductions, which may be useful on a well-posed problem but can prevent distinguishing whether a problem is infeasible or unbounded: 0 = no 1 = yes (default)Whether to exploit independent MIP sub-models: -1 = automatic choice (default) 0 = no 1 = use moderate effort 2 = use aggressive effortlimit on the number of degenerate simplex moves -- for use when too much time is taken after solving the initial root relaxation of a MIP problem and before cut generation or root heuristics have started.maximum number of cutting-plane passes to do during root-cut generation; default = -1 ==> automatic choiceIf the optimal objective value is no better than cutoff, report "objective cutoff" and do not return a solution. Default: -Infinity for minimizing, +Infinity for maximizing.maximum number of constraint aggregation passes during cut generation (-1 = default = no limit); overrides "cuts"Which child node to explore first when branching: -1 = explore "down" branch first 0 = explore "most promising" branch first (default) 1 = explore "up" branch firststrategy for initial basis construction during crossover: 0 = favor speed (default) 1 = favor numerical stabilityhow to transform a barrier solution to a basic one: -1 = automatic choice (default) 0 = none: return an interior solution 1 = push dual vars first, finish with primal simplex 2 = push dual vars first, finish with dual simplex 3 = push primal vars first, finish with primal simplex 4 = push primal vars first, finish with dual simplexhow many independent MIP solves to allow at once when multiple threads are available. The available threads are divided as evenly as possible among the concurrent solves. Default = 1.stop after a feasible solution with objective value at least as good as this value has been found.whether to return suffix .bestbound for the best known 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 an integer feasible solution has not yet been found.stop once the best bound on the objective value is at least as good as this value.whether to honor basis and solnsens when an optimal solution was not found: 0 = only if a feasible solution was found (default) 1 = yes 2 = nowhether to use or return a basis: 0 = no 1 = use incoming basis (if provided) 2 = return final basis 3 = both (1 + 2 = default) For problems with integer variables and quadratic constraints, basis = 0 is assumed quietly unless qcpdual=1 is specified.convergence tolerance on the relative difference between primal and dual objective values for barrier algorithms when solving problems with quadratic constraints (default 1e-6)Ordering used to reduce fill in sparse-matrix factorizations during the barrier algorithm: -1 = automatic choice 0 = approximate minimum degree 1 = nested dissectionLimit on the number of barrier iterations (default none)Whether to use the homogeneous barrier algorithm (e.g., when method=2 is specified): -1 = only when solving a MIP node relaxation (default) 0 = never 1 = always. The homogeneous barrier algorithm can detect infeasibility or unboundedness directly, without crossover, but is a bit slower than the nonhomogeneous barrier algorithm.Limit on the number of central corrections done in each barrier iteration (default -1 = automatic choice)tolerance on the relative difference between the primal and dual objectives for stopping the barrier algorithm (default 1e-8)stub for alternate MIP solutions. The number of alternative MIP solution files written is determined by three keywords: ams_limit gives the maximum number of files written; ams_eps gives a relative tolerance on the objective values of alternative solutions; and ams_epsabs gives an absolute tolerance on how much worse the objectives can be.search mode for MIP solutions when several are desired: 0 = just focus on finding an optimal solution (default) 1 = make some effort at finding additional solutions 2 = try to find the "ams_limit" best solutions.limit on number of alternate MIP solutions written (default = 10)absolute tolerance for reporting alternate MIP solutions (default = no limit)relative tolerance for reporting alternate MIP solutions (default = no limit)whether to use aggregation during Gurobi presolve: 0 = no (sometimes reduces numerical errors) 1 = yes (default)amount of fill allowed during aggregation during gurobi's presolve (default -1)When some variables appear in piecewise-linear terms in the objective and AMPL's "option pl_lineraize 0" is specified, lower bounds of -pl_bigm are assumed for such variables that are not bounded below and upper bounds of +pl_bigm are assumed for such variables that are not bounded above. Default = 1e6..A???Name of file containing "server = ..." and possibly values for server_password, server_port, and server_timeout. Synonyms for server: computeserver, servers. Synonym for server_password: password.Report job as rejected by Gurobi compute server if the job is not started within server_timeout seconds. Default = -1 (no limit).Priority for Gurobi compute server(s). Default = 1. Highest priority = 100.IP port to use for Gurobi compute server(s); -1 ==> use default.Password (if needed) for specified Guruobi compute server(s).Comma-separated list of Gurobi compute servers, specified either by name or by IP address. Default: run Gurobi locally (i.e., do not use a remote Gurobi server).Hoptional "machine pool" to use with Gurobi Instant Cloud.use Gurobi Instant Cloud with this "secretKey". 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