lp_solve usage

lp_solve [options] [[<]input_file]
List of options:
-h              prints this message
-v <level>      verbose mode, gives flow through the program.
                 if level not provided (-v) then -v4 (NORMAL) is taken.
         -v1: CRITICAL
         -v2: SEVERE
         -v3: IMPORTANT (default)
         -v4: NORMAL
         -v5: DETAILED
         -v6: FULL
-d              debug mode, all intermediate results are printed,
                and the branch-and-bound decisions
-p              print the values of the dual variables
-b <bound>      specify a lower bound for the objective function
                to the program. If close enough, may speed up the
-i              print all intermediate valid solutions.
                Can give you useful solutions even if the total run time
                is too long
-e <number>     specifies the epsilon which is used to determine whether a
                floating point number is in fact an integer.
                Should be < 0.5
-g <number>     specifies the MIP gap for branch-and-bound.
                This specifies the allowed tolerance on the object function.
                Can result in faster solving times.
-f              specifies that branch-and-bound algorithm stops at first found
-o <value>      specifies that branch-and-bound algorithm stops when objective
                value is better than value
-c              during branch-and-bound, take the ceiling branch first
-ca             during branch-and-bound, the algorithm chooses branch
-B <rule>       specify branch-and-bound rule
         -B0: Select Lowest indexed non-integer column (default)
         -B1: Select Random non-integer column
         -B2: Select Largest deviation from an integer value
         -B3: Select Best ???
         -B4: Select Median value deviation from an integer value
         -B5: Select Greedy ???
-piv <rule>     specify simplex pivot rule
         -piv0: Select first
         -piv3: Select most negative (default)
         -piv5: Select greedy
-s <mode>       use automatic problem scaling.
         -s0: Numerical range-based scaling
         -s1: Geometric scaling
         -s2: Curtis-reid scaling
-sp             also do power scaling.
-sl             also do Lagrange scaling.
-si             also do Integer scaling.
-I              print info after re-inverting
-t              trace pivot selection
-lp             read from LP file (default)
-mps            read from MPS file
-degen          use perturbations to reduce degeneracy,
                can increase numerical instability
-trej <Trej>    set minimum pivot value
-epsd <epsd>    set minimum tolerance for reduced costs
-epsb <epsb>    set minimum tolerance for the RHS
-epsel <epsel>  set tolerance
-parse_only     parse input file but do not calculate (i.e. check)
-presolve       presolve problem before start optimising
-improve <level>        iterative improvement level
         -improve0: none (default)
         -improve1: FTRAN only
         -improve2: BTRAN only
         -improve3: FTRAN + BTRAN
-time           Print CPU time to parse input and to calculate result.
-timeout <sec>  Timeout after sec seconds when not solution found.
-timeoutok      If timeout, take the best yet found solution.
-min            Minimize the lp problem (overrules setting in file)
-max            Maximize the lp problem (overrules setting in file)
-S <detail>     Print solution. If detail omitted, then -S2 is used.
         -S0: Print nothing
         -S1: Only objective value
         -S2: Obj value+variables (default)
         -S3: Obj value+variables+constraints
         -S4: Obj value+variables+constraints+duals
         -S5: Obj value+variables+constraints+duals+lp model
         -S6: Obj value+variables+constraints+duals+lp model+lp scales