dualB(ound) : Initially algorithm acts as if no gap between bounds exceeds this value
dualT(olerance) : For an optimal solution no dual infeasibility may exceed this value
primalT(olerance) : For a feasible solution no primal infeasibility, i.e., constraint violation, may exceed this value
primalW(eight) : Initially algorithm acts as if it costs this much to be infeasible
psi : Two-dimension pricing factor for Positive Edge criterion
zeroT(olerance) : Kill all coefficients whose absolute value is less than this value
allow(ableGap) : Stop when gap between best possible and best less than this
cuto(ff) : Bound on the objective value for all solutions
inc(rement) : A valid solution must be at least this much better than last integer solution
integerT(olerance) : For a feasible solution no integer variable may be more than this away from an integer value
preT(olerance) : Tolerance to use in presolve
pumpC(utoff) : Fake cutoff for use in feasibility pump
ratio(Gap) : Stop when gap between best possible and best known is less than this fraction of larger of two
sec(onds) : maximum seconds
force(Solution) : Whether to use given solution as crash for BAB
idiot(Crash) : Whether to try idiot crash
maxF(actor) : Maximum number of iterations between refactorizations
maxIt(erations) : Maximum number of iterations before stopping
output(Format) : Which output format to use
randomS(eed) : Random seed for Clp
slog(Level) : Level of detail in (LP) Solver output
sprint(Crash) : Whether to try sprint crash
cutD(epth) : Depth in tree at which to do cuts
cutL(ength) : Length of a cut
depth(MiniBab) : Depth at which to try mini branch-and-bound
hot(StartMaxIts) : Maximum iterations on hot start
log(Level) : Level of detail in Coin branch and Cut output
maxN(odes) : Maximum number of nodes to do
maxSaved(Solutions) : Maximum number of solutions to save
maxSo(lutions) : Maximum number of feasible solutions to get
passC(uts) : Number of rounds that cut generators are applied in the root node
passF(easibilityPump) : How many passes to do in the Feasibility Pump heuristic
passT(reeCuts) : Number of rounds that cut generators are applied in the tree
pumpT(une) : Dubious ideas for feasibility pump
randomC(bcSeed) : Random seed for Cbc
slow(cutpasses) : Maximum number of rounds for slower cut generators
strat(egy) : Switches on groups of features
strong(Branching) : Number of variables to look at in strong branching
trust(PseudoCosts) : Number of branches before we trust pseudocosts
allC(ommands) : Whether to print less used commands
chol(esky) : Which cholesky algorithm
crash : Whether to create basis for problem
cross(over) : Whether to get a basic solution with the simplex algorithm after the barrier algorithm finished
direction : Minimize or Maximize
error(sAllowed) : Whether to allow import errors
fact(orization) : Which factorization to use
keepN(ames) : Whether to keep names from import
mess(ages) : Controls if Clpnnnn is printed
perturb(ation) : Whether to perturb the problem
presolve : Whether to presolve problem
printi(ngOptions) : Print options
scal(ing) : Whether to scale problem
timeM(ode) : Whether to use CPU or elapsed time
clique(Cuts) : Whether to use Clique cuts
combine(Solutions) : Whether to use combine solution heuristic
combine2(Solutions) : Whether to use crossover solution heuristic
constraint(fromCutoff) : Whether to use cutoff as constraint
cost(Strategy) : How to use costs for branching priorities
cplex(Use) : Whether to use Cplex!
cuts(OnOff) : Switches all cut generators on or off
Dins : Whether to try Distance Induced Neighborhood Search
DivingS(ome) : Whether to try Diving heuristics
DivingC(oefficient) : Whether to try Coefficient diving heuristic
DivingF(ractional) : Whether to try Fractional diving heuristic
DivingG(uided) : Whether to try Guided diving heuristic
DivingL(ineSearch) : Whether to try Linesearch diving heuristic
DivingP(seudoCost) : Whether to try Pseudocost diving heuristic
DivingV(ectorLength) : Whether to try Vectorlength diving heuristic
dw(Heuristic) : Whether to try Dantzig Wolfe heuristic
feas(ibilityPump) : Whether to try the Feasibility Pump heuristic
flow(CoverCuts) : Whether to use Flow Cover cuts
GMI(Cuts) : Whether to use alternative Gomory cuts
gomory(Cuts) : Whether to use Gomory cuts
greedy(Heuristic) : Whether to use a greedy heuristic
heur(isticsOnOff) : Switches most primal heuristics on or off
knapsack(Cuts) : Whether to use Knapsack cuts
lagomory(Cuts) : Whether to use Lagrangean Gomory cuts
latwomir(Cuts) : Whether to use Lagrangean TwoMir cuts
lift(AndProjectCuts) : Whether to use Lift and Project cuts
local(TreeSearch) : Whether to use local tree search when a solution is found
mixed(IntegerRoundingCuts) : Whether to use Mixed Integer Rounding cuts
node(Strategy) : What strategy to use to select the next node from the branch and cut tree
PrepN(ames) : If column names will be kept in pre-processed model
pivotAndC(omplement) : Whether to try Pivot and Complement heuristic
pivotAndF(ix) : Whether to try Pivot and Fix heuristic
preprocess : Whether to use integer preprocessing
probing(Cuts) : Whether to use Probing cuts
proximity(Search) : Whether to do proximity search heuristic
randomi(zedRounding) : Whether to try randomized rounding heuristic
reduce(AndSplitCuts) : Whether to use Reduce-and-Split cuts
reduce2(AndSplitCuts) : Whether to use Reduce-and-Split cuts - style 2
residual(CapacityCuts) : Whether to use Residual Capacity cuts
Rens : Whether to try Relaxation Enforced Neighborhood Search
Rins : Whether to try Relaxed Induced Neighborhood Search
round(ingHeuristic) : Whether to use simple (but effective) Rounding heuristic
sosO(ptions) : Whether to use SOS from AMPL
sosP(rioritize) : How to deal with SOS priorities
two(MirCuts) : Whether to use Two phase Mixed Integer Rounding cuts
Vnd(VariableNeighborhoodSearch) : Whether to try Variable Neighborhood Search
zero(HalfCuts) : Whether to use zero half cuts
allS(lack) : Set basis back to all slack and reset solution
barr(ier) : Solve using primal dual predictor corrector algorithm
basisI(n) : Import basis from bas file
basisO(ut) : Export basis as bas file
directory : Set Default directory for import etc.
dualS(implex) : Do dual simplex algorithm
either(Simplex) : Do dual or primal simplex algorithm
end : Stops clp execution
exit : Stops clp execution
export : Export model as mps file
gsolu(tion) : Puts glpk solution to file
guess : Guesses at good parameters
help : Print out version, non-standard options and some help
import : Import model from mps file
initialS(olve) : Solve to continuous
max(imize) : Set optimization direction to maximize
min(imize) : Set optimization direction to minimize
para(metrics) : Import data from file and do parametrics
primalS(implex) : Do primal simplex algorithm
printM(ask) : Control printing of solution on a mask
quit : Stops clp execution
restoreS(olution) : reads solution from file
saveS(olution) : saves solution to file
solu(tion) : Prints solution to file
stat(istics) : Print some statistics
stop : Stops clp execution
branch(AndCut) : Do Branch and Cut
doH(euristic) : Do heuristics before any preprocessing
mips(tart) : reads an initial feasible solution from file
nextB(estSolution) : Prints next best saved solution to file
prio(rityIn) : Import priorities etc from file
solv(e) : Solve problem