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LP parameters

LP_verbosity - integer (0).

Verbosity level of the LP module.

set_obj_upper_lim - boolean (FALSE).

Whether to stop solving the LP relaxation when it's optimal value is provably higher than the global upper bound. There are some advantages to continuing the solution process anyway. For instance, this results in the highest possible lower bound. On the other hand, if the matrix is full, this node will be pruned anyway and the rest of the computation is pointless. This option should be set at FALSE for column generation since the LP dual values may not be reliable otherwise.

try_to_recover_from_error - boolean (TRUE).

Indicates what should be done in case the LP solver is unable to solve a particular LP relaxation because of numerical problems. It is possible to recover from this situation but further results may be suspect. On the other hand, the entire solution process can be abandoned.

problem_type - integer (ZERO_ONE_PROBLEM{0}).

The type of problem being solved. Other values are INTEGER_PROBLEM{1} or MIXED_INTEGER_PROBLEM{2}. (Caution: The mixed-integer option is not well tested.)

cut_pool_check_frequency - integer (10).

The number of iterations between sending LP solutions to the cut pool to find violated cuts. It is not advisable to check the cut pool too frequently as the cut pool module can get bogged down and the LP solution generally do not change that drastically from one iteration to the next anyway.

not_fixed_storage_size - integer (2048).

The not fixed list is a partial list of indices of variables not in the matrix that have not been fixed by reduced cost. Keeping this list allows SYMPHONY to avoid repricing variables (an expensive operation) that are not in the matrix because they have already been permanently fixed. When this array reaches its maximum size, no more variable indices can be stored. It is therefore advisable to keep the maximum size of this array as large as possible, given memory limitations.

max_non_dual_feas_to_add_min, max_non_dual_feas_to_add_max, max_non_dual_feas_to_add_frac -

integer, integer, double (20, 200, .05). These three parameters determine the maximum number of non-dual-feasible columns that can be added in any one iteration after pricing. This maximum is set to the indicated fraction of the current number of active columns unless this numbers exceeds the given maximum or is less than the given minimum, in which case, it is set to the max or min, respectively.

max_not_fixable_to_add_min, max_not_fixable_to_add_max, max_not_fixable_to_add_frac -

integer, integer, double (100, 500, .1). As above, these three parameters determine the maximum number of new columns to be added to the problem because they cannot be priced out. These variables are only added when trying to restore infeasibility and usually, this does not require many variables anyway.

mat_col_compress_num, mat_col_compress_ratio - integer, double (50, .05).

Determines when the matrix should be physically compressed. This only happens when the number of columns is high enough to make it ``worthwhile.'' The matrix is physically compressed when the number of deleted columns exceeds either an absolute number and a specified fraction of the current number of active columns.

mat_row_compress_num, mat_row_compress_ratio - integer, double (20, .05).

Same as above except for rows.

tailoff_gap_backsteps, tailoff_gap_frac - integer, double (2, .99).

Determines when tailoff is detected in the LP module. Tailoff is reported if the average ratio of the current gap to the previous iteration's gap over the last tailoff_gap_backsteps iterations wasn't at least tailoff_gap_frac.

tailoff_obj_backsteps, tailoff_obj_frac - integer, double (2, .99).

Same as above, only the ratio is taken with respect to the change in objective function values instead of the change in the gap.

ineff_cnt_to_delete - integer (0).

Determines after how many iterations of being deemed ineffective a constraint is removed from the current relaxation.

eff_cnt_before_cutpool - integer (3).

Determines after how many iterations of being deemed effective each cut will be sent to the global pool.

ineffective_constraints - integer (BASIC_SLACKS_ARE_INEFFECTIVE{2}).

Determines under what condition a constraint is deemed ineffective in the current relaxation. Other possible values are NO_CONSTRAINT_IS_INEFFECTIVE{0}, NONZERO_SLACKS_ARE_INEFFECTIVE{1}, and
ZERO_DUAL_VALUES_ARE_INEFFECTIVE{3}.

base_constraints_always_effective - boolean (TRUE).

Determines whether the base constraints can ever be removed from the relaxation. In some case, removing the base constraints from the problem can be disastrous depending on the assumptions made by the cut generator.

branch_on_cuts - boolean (FALSE).

This informs the framework whether the user plans on branching on cuts or not. If so, there is additional bookkeeping to be done, such as maintaining a pool of slack cuts to be used for branching. Therefore, the user should not set this flag unless he actually plans on using this feature.

discard_slack_cuts - integer (DISCARD_SLACKS_BEFORE_NEW_ITERATION{0}).

Determines when the pool of slack cuts is discarded. The other option is DISCARD_SLACKS_WHEN_STARTING_NEW_NODE{1}.

first_lp_first_cut_time_out, first_lp_all_cuts_time_out, later_lp_first_cut_time_out,

later_lp_all_cuts_time_out - double (0, 0, 5, 1). The next group of parameters determines when the LP should give up waiting for cuts from the cut generator and start to solve the relaxation in its current form or possibly branch if necessary. There are two factors that contribute to determining this timeout. First is whether this is the first LP in the search node of whether it is a later LP. Second is whether any cuts have been added already in this iteration. The four timeout parameters correspond to the four possible combinations of these two variables.

no_cut_timeout -

This keyword does not have an associated value. If this keyword appears on a line by itself or with a value, this tells the framework not to time out while waiting for cuts. This is useful for debugging since it enables runs with a single LP module to be duplicated.

all_cut_timeout - double (no default).

This keyword tells the framework to set all of the above timeout parameters to the value indicated.

max_cut_num_per_iter - integer (20).

The maximum number of cuts that can be added to the LP in an iteration. The remaining cuts stay in the local pool to be added in subsequent iterations, if they are strong enough.

do_reduced_cost_fixing - boolean (FALSE).

Whether or not to attempt to fix variables by reduced cost. This option is highly recommended

gap_as_ub_frac, gap_as_last_gap_frac - double (.1, .7).

Determines when reduced cost fixing should be attempted. It is only done when the gap is within the fraction gap_as_ub_frac of the upper bound or when the gap has decreased by the fraction gap_as_last_gap_frac since the last time variables were fixed.

do_logical_fixing - boolean (FALSE).

Determines whether the user's logical fixing routine should be used.

fixed_to_ub_before_logical_fixing, fixed_to_ub_frac_before_logical_fixing

- integer, double (1, .01). Determines when logical fixing should be attempted. It will be called only when a certain absolute number and a certain number of variables have been fixed to their upper bounds by reduced cost. This is because it is typically only after fixing variables to their upper bound that other variables can be logically fixed.

max_presolve_iter - integer (10).

Number of simplex iterations to be performed in the pre-solve for strong branching.

strong_branching_cand_num_max, strong_branching_cand_num_min, strong_branching_red_ratio

- integer (25, 5, 1). These three parameters together determine the number of strong branching candidates to be used by default. In the root node, strong_branching_cand_num_max candidates are used. On each succeeding level, this number is reduced by the number strong_branching_red_ratio multiplied by the square of the level. This continues until the number of candidates is reduced to strong_branching_cand_num_min and then that number of candidates is used in all lower levels of the tree.

is_feasible_default - integer (TEST_INTEGRALITY{1}).

Determines the default test to be used to determine feasibility. This parameter is provided so that the user can change the default behavior without recompiling. The only other option is TEST_ZERO_ONE{0}.

send_feasible_solution_default - integer (SEND_NONZEROS{0}).

Determines the form in which to send the feasible solution. This parameter is provided so that the user can change the default behavior without recompiling. This is currently the only option.

send_lp_solution_default - integer (SEND_NONZEROS{0}).

Determines the default form in which to send the LP solution to the cut generator and cut pool. This parameter is provided so that the user can change the default behavior without recompiling. The other option is SEND_FRACTIONS{1}.

display_solution_default - integer (DISP_NOTHING{0}).

Determines how to display the current LP solution if desired. See the description of user_display_solution() for other possible values. This parameter is provided so that the user can change the default behavior without recompiling.

shall_we_branch_default - integer (USER__BRANCH_IF_MUST{2}).

Determines the default branching behavior. Other values are USER__DO_NOT_BRANCH{0} (not recommended as a default), USER__DO_BRANCH{1} (also not recommended as a default), and USER__BRANCH_IF_TAILOFF{3}. This parameter is provided so that the user can change the default behavior without recompiling.

select_candidates_default - integer (USER__CLOSE_TO_HALF_AND_EXPENSIVE{11}).

Determines the default rule for selecting strong branching candidates. Other values are USER__CLOSE_TO_HALF{10} and USER__CLOSE_TO_ONE_AND_CHEAP{12}. This parameter is provided so that the user can change the default behavior without recompiling.

compare_candidates_default - integer (LOWEST_LOW_OBJ{1}).

Determines the default rule for comparing candidates. See the description of user_compare_candidates() for other values. This parameter is provided so that the user can change the default behavior without recompiling.

select_child_default - integer (PREFER_LOWER_OBJ_VALUE{0}).

Determines the default rule for selecting the child to be processed next. For other possible values, see the description user_select_child(). This parameter is provided so that the user can change the default behavior without recompiling.