Master module parameters

M_verbosity – integer (0).

M_random_seed – integer (17).

A random seed just for the Master module.

upper_bound – double (no upper bound).

This parameter is used if the user wants to artificially impose an upper bound (for instance if a solution of that value is already known).

lower_bound – double (no lower bound).

This parameter is used if the user wants to artificially impose a lower bound.

upper_bound_estimate – double (no estimate).

This parameter is used if the user wants to provide an estimate of the optimal value which will help guide the search. This is used in conjunction with the diving strategy BEST_ESTIMATE.

tm_exe, dg_exe – strings (“tm”, “dg”).

The name of the executable files of the TM and DG modules. Note that the TM executable name may have extensions that depend on the configuration of the modules, but the default is always set to the file name produced by the makefile. If you change the name of the treemanager executable from the default, you must set this parameter to the new name.

tm_debug, dg_debug – boolean (both FALSE).

Whether these modules should be started under a debugger or not (see 5.6.2 for more details on this).

tm_machine – string (empty string).

On which processor of the virtual machine the TM should be run. Leaving this parameter as an empty string means arbitrary selection.

do_draw_graph – boolean (FALSE).

Whether to start up the DG module or not (see Section 5.6.4 for an introduction to this).

do_branch_and_cut – boolean (TRUE).

Whether to run the branch and cut algorithm or not. (Set this to FALSE to run the user's heuristics only.)

mc_search_order – integer (MC_FIFO).

Use the fifo (MC_FIFO) or lifo (MC_LIFO) searh order during the multi criteria solution procedure.

mc_warm_start – boolean(FALSE).

Whether to solve the corresponding problem of each iteration from a warm start loaded from a base iteration (which is the first iteration where gamma = 1.0 and tau = 0.0) or from scratch. Currently, this option is supported if only the supported solutions are desired to be found.

trim_warm_tree – boolean(FALSE).

Whether to trim the warm start tree before re-solving. This consists of locating nodes whose descendants are all likely to be pruned in the resolve and eliminating those descendants in favor of processing the parent node itself.

mc_compare_solution_tolerance – double(0.001).

If the difference between the objective values of two solutions to be compared, during the bicriteria solution procedure, are less than this tolerance, then assume them to be equal.

mc_binary_search_tolerance – double(0).

The tolerance to be used to differentiate the gamma values if binary search is used during the bicriteria solution procedure. A value greater than zero will cause the binary search to be activated.

prep_level – integer(5).

Determines the level of preprocessing that should be done on the current MILP instance. A level of less than 0 means that no preprocessing will be done. At level $2$ basic presolve routines are used. At higher levels more advanced routines are deployed. At level $5$, valid implications are derived.

prep_dive_level – integer(5).

When a variable has been modified by preprocessing, then these changes can be used to improve other variables and constraints in the instance as well. This parameter controls how many times can we recursively try to improve the instance if a change is made.

prep_impl_dive_level – integer(0).

In some advanced preprocessing routines, a variable or constraint is modified to check what implications can be derived from that change. When such an implication is derived, it can recursively lead to more implications. This parameter controls how many levels of recursion are allowed.

prep_impl_limit – integer(50).

Determines the maximum number of implications that can be derived from preprocessing.

prep_do_probing – integer(1).

Determines if probing is used while preprocessing. Probing is not yet implemented and this parameter does not have any effect.

prep_verbosity – integer(1).

Determines the verbosity of messages from the preprocessing stage. Higher levels will produce more verbose messages.

prep_reduce_mip – boolean (1).

If some variables and constraints have been eliminated in preprocessing and if prep_reduce_mip is $1$, then the memory allocated for these deleted variables and constraints is freed. Otherwise, these are retained in the instance but are never used.

prep_probing_verbosity – integer(0).

Determines the verbosity of messages from probing stage. Probing is not yet implemented and this parameter does not have any effect.

prep_probing_level – integer(1).

Determines the maximum level of probing that is carried out before preprocessing is stopped. Probing is not yet implemented and this parameter does not have any effect.

prep_display_stats – boolean (0).

Determines if statistics on how many of each type of changes were made in the preprocessing stage are displayed ($1$) or not (0).

keep_row_ordered – integer(1).

When the value of this parameter is 1, a row ordered matrix is also retained for use after the preprocessing stage. This capability is not yet implemented and this parameter does not have any effect.

prep_do_sr – boolean (0).

When the value of this parameter is 1, additional preprocessing is performed by solving an LP with one constraint. This procedure is not thoroughly tested.

max_sr_cnt – integer(5).

This parameter controls the number of single-constraint LPs that are solved for each constraint in the preprocessing stage. This procedure is not thoroughly tested.

max_aggr_row_cnt – integer(0).

This parameter is not used and has no effect.

prep_iter_limit – integer(10).

Determines the maximum number of times preprocessing can be done on an instance. If an instance has been modified by preprocessing, then the new problem can be preprocessed again to get an even better formulation. This parameter puts a limit on the number of times such preprocessing can be done.

write_mps – boolean (0).

Determines if an MPS file be written after all preprocessing has been performed. This can be used for debugging or if the user wants to save the preprocessed instance.

write_lp – boolean (0).

Determines if an LP file be written after all preprocessing has been performed. This can be used for debugging or if the user wants to save the preprocessed instance.

prep_time_limit – integer(50).

Determines the maximum time in seconds that can be spent in preprocessing.