# is presolver coefftightening enabled  [Boolean: {0,1}]
coefftightening.enabled = 1

# is the iteration over the rows in coefftightening parallelised? [Boolean: {0,1}]
coefftightening.parallel = 1

# is presolver colsingleton enabled  [Boolean: {0,1}]
colsingleton.enabled = 1

# is presolver domcol enabled  [Boolean: {0,1}]
domcol.enabled = 1

# is presolver doubletoneq enabled  [Boolean: {0,1}]
doubletoneq.enabled = 1

# is the iteration over the rows in doubletoneq parallelised? [Boolean: {0,1}]
doubletoneq.parallel = 0

# is presolver dualfix enabled  [Boolean: {0,1}]
dualfix.enabled = 1

# is the iteration over the columns in dualfix parallelised? [Boolean: {0,1}]
dualfix.parallel = 0

# is presolver dualinfer enabled  [Boolean: {0,1}]
dualinfer.enabled = 1

# is presolver fixcontinuous enabled  [Boolean: {0,1}]
fixcontinuous.enabled = 1

# is presolver implint enabled  [Boolean: {0,1}]
implint.enabled = 1

# is the iteration over the rows in implied integer parallelised? [Boolean: {0,1}]
implint.parallel = 0

# verbosity to be used: 0 - quiet, 1 - errors, 2 - warnings, 3 - normal, 4 - detailed  [Integer: [0,4]]
message.verbosity = 3

# epsilon tolerance to consider two values equal  [Numerical: [0,0.10000000000000001]]
numerics.epsilon = 1.0000000000000001e-09

# the feasibility tolerance  [Numerical: [0,0.10000000000000001]]
numerics.feastol = 9.9999999999999995e-07

# absolute bound value that is considered too huge for activitity based calculations  [Numerical: [0,1.7976931348623157e+308]]
numerics.hugeval = 100000000

# is presolver parallelcols enabled  [Boolean: {0,1}]
parallelcols.enabled = 1

# is presolver parallelrows enabled  [Boolean: {0,1}]
parallelrows.enabled = 1

# abort factor of weighted number of reductions for presolving  [Numerical: [0,1]]
presolve.abortfac = 0.00080000000000000004

# relax bounds of implied free variables after presolving  [Boolean: {0,1}]
presolve.boundrelax = 0

# maximum number of integral variables for trying to solve disconnected components of the problem in presolving (-1: disabled)  [Integer: [-1,2147483647]]
presolve.componentsmaxint = 0

# compress the problem if fewer than compressfac times the number of rows or columns are active  [Numerical: [0,1]]
presolve.compressfac = 0.84999999999999998

# detect and remove linearly dependent equations and free columns (0: off, 1: for LPs, 2: always)  [Integer: [0,2]]
presolve.detectlindep = 1

# 0: disable dual reductions, 1: allow dual reductions that never cut off optimal solutions, 2: allow all dual reductions  [Integer: [0,2]]
presolve.dualreds = 2

# abort factor of weighted number of reductions for presolving LPs  [Numerical: [0,1]]
presolve.lpabortfac = 0.01

# maximal number of rounds (-1: unlimited, 0: cleanup) [Integer: [-1,2147483647]]
presolve.maxrounds = -1

# minimum absolute coefficient value allowed in matrix, before it is set to zero  [Numerical: [0,0.10000000000000001]]
presolve.minabscoeff = 1e-10

# random seed value  [Integer: [0,4294967295]]
presolve.randomseed = 0

# remove slack variables in equations  [Boolean: {0,1}]
presolve.removeslackvars = 1

# maximal number of threads to use (0: automatic)  [Integer: [0,2147483647]]
presolve.threads = 0

# if only one thread (presolve.threads = 1) is used, apply the reductions immediately afterwards
presolve.apply_results_immediately_if_run_sequentially = 1

# time limit for presolve  [Numerical: [0,1.7976931348623157e+308]]
presolve.tlim = 1.7976931348623157e+308

# weaken bounds obtained by constraint propagation by this factor of the feasibility tolerance if the problem is an LP  [Integer: [-2147483648,2147483647]]
presolve.weakenlpvarbounds = 0

# is presolver probing enabled  [Boolean: {0,1}]
probing.enabled = 1

# maximum number of probing candidates probed in the first badge of candidates  [Integer: [1,2147483647]]
probing.maxinitialbadgesize = 1000

# minimum number of probing candidates probed in a single badge of candidates  [Integer: [1,2147483647]]
probing.minbadgesize = 10

# minimum fraction of domain that needs to be reduced for continuous variables to accept a bound change in probing  [Numerical: [0,1]]
probing.mincontdomred = 0.29999999999999999

# is presolver propagation enabled  [Boolean: {0,1}]
propagation.enabled = 1

# is the iteration over the rows in propagation parallelised? [Boolean: {0,1}]
propagation.parallel = 1

# is presolver simpleprobing enabled  [Boolean: {0,1}]
simpleprobing.enabled = 1

# is the iteration over the rows in simpleprobing parallelised? [Boolean: {0,1}]
simpleprobing.parallel = 0

# is presolver simplifyineq enabled  [Boolean: {0,1}]
simplifyineq.enabled = 1

# is the iteration over the rows in simplifyineq parallelised?    [Boolean: {0,1}]
simplifyineq.parallel = 1

# is presolver sparsify enabled  [Boolean: {0,1}]
sparsify.enabled = 1

# maximum absolute scale to use for cancelling nonzeros  [Numerical: [1,1.7976931348623157e+308]]
sparsify.maxscale = 1000

# is presolver stuffing enabled  [Boolean: {0,1}]
stuffing.enabled = 1

# should substitution of binary variables with general integers be allowed  [Boolean: {0,1}]
substitution.binarieswithints = 1

# is presolver substitution enabled  [Boolean: {0,1}]
substitution.enabled = 1

# markowitz tolerance value for allowing a substitution  [Numerical: [0,1]]
substitution.markowitz_tolerance = 0.01

# maximum estimated fillin for variable substitutions  [Integer: [0,2147483647]]
substitution.maxfillin = 10

# maximum amount of nonzeros being moved to make space for fillin from substitutions within a row  [Integer: [0,2147483647]]
substitution.maxshiftperrow = 10

# should the basis be calculated during postsolve? Deactivates variable bound tightening due to computational overhead.
calculate_basis_for_dual = 1

# should the primal/dual solution be validated during after every postsolving step?
validation_after_every_postsolving_step = 0

# should PaPILO print a VeriPB log (only for PseudoBoolean problems)?
verification_with_VeriPB = 0

# how to log the proof of verification? 0: reverse unit propagation, 1: Addition in polish notation
veripb.verify_propagation = 0

# defines the offset for bound tightening
bound_tightening_offset = 0.0001

# PaPILO resumes with the next higher complexity class if the last n rounds only consisted of bound changes (-1 deactivated) [Integer: [-1,2147483647]]
max_consecutive_rounds_of_only_bound_changes = 500

# should ParallelCols search for symmetries at the end (for example for binary problems where merging columns does not work)
parallelcols.symmetries_enabled = 0
