Date: 2010-02-14 11:57:00

# `BONMIN` Users' Manual

Introduction | Download | Install | Use | Setting Options | Options List | Bibliography |

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## List of BONMIN options

Option | type | B-BB | B-OA | B-QG | B-Hyb | B-Ecp | B-iFP | Cbc_D
Algorithm choice
algorithm | S | + | + | + | + | + | + | +
Branch-and-bound options
allowable_fraction_gap | F | + | + | + | + | + | + | +
allowable_gap | F | + | + | + | + | + | + | +
cutoff | F | + | + | + | + | + | + | +
cutoff_decr | F | + | + | + | + | + | + | +
enable_dynamic_nlp | S | - | - | + | + | + | - | -
integer_tolerance | F | + | + | + | + | + | + | +
iteration_limit | I | + | + | + | + | + | + | +
nlp_failure_behavior | S | + | - | - | - | - | - | -
node_comparison | S | + | + | + | + | + | + | -
node_limit | I | + | + | + | + | + | + | +
num_cut_passes | I | - | - | + | + | + | - | -
num_cut_passes_at_root | I | - | - | + | + | + | - | -
number_before_trust | I | + | + | + | + | + | + | +
number_strong_branch | I | + | + | + | + | + | + | +
solution_limit | I | + | + | + | + | + | + | +
sos_constraints | S | + | + | + | + | + | + | -
time_limit | F | + | + | + | + | + | + | +
tree_search_strategy | S | + | + | + | + | + | + | -
variable_selection | S | + | - | - | - | - | - | -
MILP cutting planes in hybrid
2mir_cuts | I | - | + | + | + | + | + | +
Gomory_cuts | I | - | + | + | + | + | + | +
clique_cuts | I | - | + | + | + | + | + | +
cover_cuts | I | - | + | + | + | + | + | +
flow_cover_cuts | I | - | + | + | + | + | + | +
lift_and_project_cuts | I | - | + | + | + | + | + | +
mir_cuts | I | - | + | + | + | + | + | +
reduce_and_split_cuts | I | - | + | + | + | + | + | +
MINLP Heuristics
feasibility_pump_objective_norm | I | + | + | + | + | + | + | -
heuristic_RINS | S | + | + | + | + | + | + | -
heuristic_dive_MIP_vectorLength | S | + | + | + | + | + | + | -
heuristic_dive_fractional | S | + | + | + | + | + | + | -
heuristic_dive_vectorLength | S | + | + | + | + | + | + | -
heuristic_feasibility_pump | S | + | + | + | + | + | + | -
pump_for_minlp | S | + | + | + | + | + | + | -
MINLP heuristics
heuristic_dive_MIP_fractional | S | + | + | + | + | + | + | -
Nlp solution robustness
max_consecutive_failures | I | + | - | - | - | - | - | -
max_random_point_radius | F | + | - | - | - | - | - | -
num_iterations_suspect | I | + | + | + | + | + | + | +
num_retry_unsolved_random_point | I | + | + | + | + | + | + | +
random_point_perturbation_interval | F | + | - | - | - | - | - | -
random_point_type | S | + | - | - | - | - | - | -
Nlp solve options in B-Hyb
nlp_solve_frequency | I | - | - | - | + | - | - | -
nlp_solve_max_depth | I | - | - | - | + | - | - | -
nlp_solves_per_depth | F | - | - | - | + | - | - | -
Options for MILP solver
milp_log_level | I | - | - | - | - | - | - | +
milp_solver | S | - | - | - | - | - | - | +
Options for OA decomposition
oa_decomposition | S | - | - | + | + | + | - | -
oa_log_frequency | F | + | - | - | + | + | - | -
oa_log_level | I | + | - | - | + | + | - | -
Options for ecp cuts generation
ecp_abs_tol | F | - | - | + | + | - | - | -
ecp_max_rounds | I | - | - | + | + | - | - | -
ecp_propability_factor | F | - | - | + | + | - | - | -
ecp_rel_tol | F | - | - | + | + | - | - | -
filmint_ecp_cuts | I | - | - | + | + | - | - | -
Options for feasibility checker using OA cuts
feas_check_cut_types | S | - | - | + | + | + | - | -
feas_check_discard_policy | S | - | - | + | + | + | - | -
generate_benders_after_so_many_oa | I | - | - | + | + | + | - | -
Options for feasibility pump
fp_log_frequency | F | - | - | + | + | - | - | -
fp_log_level | I | - | - | + | + | - | - | -
Options for non-convex problems
coeff_var_threshold | F | + | - | - | - | - | - | -
dynamic_def_cutoff_decr | S | + | - | - | - | - | - | -
first_perc_for_cutoff_decr | F | + | - | - | - | - | - | -
max_consecutive_infeasible | I | + | - | - | - | - | - | -
num_resolve_at_infeasibles | I | + | - | - | - | - | - | -
num_resolve_at_node | I | + | - | - | - | - | - | -
num_resolve_at_root | I | + | - | - | - | - | - | -
second_perc_for_cutoff_decr | F | + | - | - | - | - | - | -
Outer Approximation cuts generation
add_only_violated_oa | S | - | + | + | + | + | + | +
oa_cuts_log_level | I | - | + | + | + | + | + | +
oa_cuts_scope | S | - | + | + | + | + | + | +
tiny_element | F | - | + | + | + | + | + | +
very_tiny_element | F | - | + | + | + | + | + | +
Output ond log-levels options
bb_log_interval | I | + | + | + | + | + | + | +
bb_log_level | I | + | + | + | + | + | + | +
lp_log_level | I | - | + | + | + | + | + | +
nlp_log_at_root | I | + | + | + | + | + | + | -
Strong branching setup
candidate_sort_criterion | S | + | + | + | + | + | + | -
maxmin_crit_have_sol | F | + | + | + | + | + | + | -
maxmin_crit_no_sol | F | + | + | + | + | + | + | -
min_number_strong_branch | I | + | + | + | + | + | + | -
number_before_trust_list | I | + | + | + | + | + | + | -
number_look_ahead | I | + | + | + | + | + | - | -
number_strong_branch_root | I | + | + | + | + | + | + | -
setup_pseudo_frac | F | + | + | + | + | + | + | -
trust_strong_branching_for_pseudo_cost | S | + | + | + | + | + | + | -
nlp interface option
file_solution | S | + | + | + | + | + | + | +
nlp_log_level | I | + | + | + | + | + | + | +
nlp_solver | S | + | + | + | + | + | + | +
warm_start | S | + | - | - | - | - | - | -

### Algorithm choice

algorithm: Choice of the algorithm.
This will preset some of the options of bonmin depending on the algorithm choice. The default value for this string option is ”B-BB”.
Possible values:

- B-BB: simple branch-and-bound algorithm,
- B-OA: OA Decomposition algorithm,
- B-QG: Quesada and Grossmann branch-and-cut algorithm,
- B-Hyb: hybrid outer approximation based branch-and-cut,
- B-Ecp: ecp cuts based branch-and-cut a la FilMINT.
- B-iFP: Iterated Feasibility Pump for MINLP.

### Branch-and-bound options

allowable_fraction_gap: Specify the value of relative gap under which the algorithm stops.
Stop the tree search when the gap between the objective value of the best known solution and the best bound on the objective of any solution is less than this fraction of the absolute value of the best known solution value. The valid range for this real option is -1 ⋅ 10+20 ≤ allowable_fraction_gap ≤ 1 ⋅ 10+20 and its default value is 0.

allowable_gap: Specify the value of absolute gap under which the algorithm stops.
Stop the tree search when the gap between the objective value of the best known solution and the best bound on the objective of any solution is less than this. The valid range for this real option is -1 ⋅ 10+20 ≤ allowable_gap ≤ 1 ⋅ 10+20 and its default value is 0.

cutoff: Specify cutoff value.
cutoff should be the value of a feasible solution known by the user (if any). The algorithm will only look for solutions better than cutoof. The valid range for this real option is -1 ⋅ 10+100 ≤ cutoff ≤ 1 ⋅ 10+100 and its default value is 1 ⋅ 10+100.

cutoff_decr: Specify cutoff decrement.
Specify the amount by which cutoff is decremented below a new best upper-bound (usually a small positive value but in non-convex problems it may be a negative value). The valid range for this real option is -1 ⋅ 10+10 ≤ cutoff_decr ≤ 1 ⋅ 10+10 and its default value is 1 ⋅ 10-05.

enable_dynamic_nlp: Enable dynamic linear and quadratic rows addition in nlp
The default value for this string option is ”no”.
Possible values:

- no:
- yes:

integer_tolerance: Set integer tolerance.
Any number within that value of an integer is considered integer. The valid range for this real option is 0 < integer_tolerance < +inf and its default value is 1 ⋅ 10-06.

iteration_limit: Set the cumulated maximum number of iteration in the algorithm used to process nodes continuous relaxations in the branch-and-bound.
value 0 deactivates option. The valid range for this integer option is 0 ≤ iteration_limit < +inf and its default value is 2147483647.

nlp_failure_behavior: Set the behavior when an NLP or a series of NLP are unsolved by Ipopt (we call unsolved an NLP for which Ipopt is not able to guarantee optimality within the specified tolerances).
If set to ”fathom”, the algorithm will fathom the node when Ipopt fails to find a solution to the nlp at that node whithin the specified tolerances. The algorithm then becomes a heuristic, and the user will be warned that the solution might not be optimal. The default value for this string option is ”stop”.
Possible values:

- stop: Stop when failure happens.
- fathom: Continue when failure happens.

node_comparison: Choose the node selection strategy.
Choose the strategy for selecting the next node to be processed. The default value for this string option is ”best-bound”.
Possible values:

- best-bound: choose node with the smallest bound,
- depth-first: Perform depth first search,
- breadth-first: Perform breadth first search,
- dynamic: Cbc dynamic strategy (starts with a depth first search and turn to best bound after 3 integer feasible solutions have been found).
- best-guess: choose node with smallest guessed integer solution

node_limit: Set the maximum number of nodes explored in the branch-and-bound search.
The valid range for this integer option is 0 ≤ node_limit < +inf and its default value is 2147483647.

num_cut_passes: Set the maximum number of cut passes at regular nodes of the branch-and-cut.
The valid range for this integer option is 0 ≤ num_cut_passes < +inf and its default value is 1.

num_cut_passes_at_root: Set the maximum number of cut passes at regular nodes of the branch-and-cut.
The valid range for this integer option is 0 ≤ num_cut_passes_at_root < +inf and its default value is 20.

number_before_trust: Set the number of branches on a variable before its pseudo costs are to be believed in dynamic strong branching.
A value of 0 disables pseudo costs. The valid range for this integer option is 0 ≤ number_before_trust < +inf and its default value is 8.

number_strong_branch: Choose the maximum number of variables considered for strong branching.
Set the number of variables on which to do strong branching. The valid range for this integer option is 0 ≤ number_strong_branch < +inf and its default value is 20.

solution_limit: Abort after that much integer feasible solution have been found by algorithm
value 0 deactivates option The valid range for this integer option is 0 ≤ solution_limit < +inf and its default value is 2147483647.

sos_constraints: Wether or not to activate SOS constraints.
(only type 1 SOS are supported at the moment) The default value for this string option is ”enable”.
Possible values:

- enable:
- disable:

time_limit: Set the global maximum computation time (in secs) for the algorithm.
The valid range for this real option is 0 ≤ time_limit < +inf and its default value is 1 ⋅ 10+10.

tree_search_strategy: Pick a strategy for traversing the tree
All strategies can be used in conjunction with any of the node comparison functions. Options which affect dfs-dive are max-backtracks-in-dive and max-dive-depth. The dfs-dive won’t work in a non-convex problem where objective does not decrease down branches. The default value for this string option is ”probed-dive”.
Possible values:

- top-node: Always pick the top node as sorted by the node comparison function
- dive: Dive in the tree if possible, otherwise pick top node as sorted by the tree comparison function.
- probed-dive: Dive in the tree exploring two childs before continuing the dive at each level.
- dfs-dive: Dive in the tree if possible doing a depth first search. Backtrack on leaves or when a prescribed depth is attained or when estimate of best possible integer feasible solution in subtree is worst than cutoff. Once a prescribed limit of backtracks is attained pick top node as sorted by the tree comparison function
- dfs-dive-dynamic: Same as dfs-dive but once enough solution are found switch to best-bound and if too many nodes switch to depth-first.

variable_selection: Chooses variable selection strategy
The default value for this string option is ”strong-branching”.
Possible values:

- most-fractional: Choose most fractional variable
- strong-branching: Perform strong branching
- reliability-branching: Use reliability branching
- curvature-estimator: Use curvature estimation to select branching variable
- qp-strong-branching: Perform strong branching with QP approximation
- lp-strong-branching: Perform strong branching with LP approximation
- nlp-strong-branching: Perform strong branching with NLP approximation
- osi-simple: Osi method to do simple branching
- osi-strong: Osi method to do strong branching
- random: Method to choose branching variable randomly

### MILP cutting planes in hybrid

2mir_cuts: Frequency (in terms of nodes) for generating 2-MIR cuts in branch-and-cut
If k ¿ 0, cuts are generated every k nodes, if -99 ¡ k ¡ 0 cuts are generated every -k nodes but Cbc may decide to stop generating cuts, if not enough are generated at the root node, if k=-99 generate cuts only at the root node, if k=0 or 100 do not generate cuts. The valid range for this integer option is -100 ≤ 2mir_cuts < +inf and its default value is 0.

Gomory_cuts: Frequency k (in terms of nodes) for generating Gomory cuts in branch-and-cut.
If k ¿ 0, cuts are generated every k nodes, if -99 ¡ k ¡ 0 cuts are generated every -k nodes but Cbc may decide to stop generating cuts, if not enough are generated at the root node, if k=-99 generate cuts only at the root node, if k=0 or 100 do not generate cuts. The valid range for this integer option is -100 ≤ Gomory_cuts < +inf and its default value is -5.

clique_cuts: Frequency (in terms of nodes) for generating clique cuts in branch-and-cut
If k ¿ 0, cuts are generated every k nodes, if -99 ¡ k ¡ 0 cuts are generated every -k nodes but Cbc may decide to stop generating cuts, if not enough are generated at the root node, if k=-99 generate cuts only at the root node, if k=0 or 100 do not generate cuts. The valid range for this integer option is -100 ≤ clique_cuts < +inf and its default value is -5.

cover_cuts: Frequency (in terms of nodes) for generating cover cuts in branch-and-cut
If k ¿ 0, cuts are generated every k nodes, if -99 ¡ k ¡ 0 cuts are generated every -k nodes but Cbc may decide to stop generating cuts, if not enough are generated at the root node, if k=-99 generate cuts only at the root node, if k=0 or 100 do not generate cuts. The valid range for this integer option is -100 ≤ cover_cuts < +inf and its default value is -5.

flow_cover_cuts: Frequency (in terms of nodes) for generating flow cover cuts in branch-and-cut
If k ¿ 0, cuts are generated every k nodes, if -99 ¡ k ¡ 0 cuts are generated every -k nodes but Cbc may decide to stop generating cuts, if not enough are generated at the root node, if k=-99 generate cuts only at the root node, if k=0 or 100 do not generate cuts. The valid range for this integer option is -100 ≤ flow_cover_cuts < +inf and its default value is -5.

lift_and_project_cuts: Frequency (in terms of nodes) for generating lift-and-project cuts in branch-and-cut
If k ¿ 0, cuts are generated every k nodes, if -99 ¡ k ¡ 0 cuts are generated every -k nodes but Cbc may decide to stop generating cuts, if not enough are generated at the root node, if k=-99 generate cuts only at the root node, if k=0 or 100 do not generate cuts. The valid range for this integer option is -100 ≤ lift_and_project_cuts < +inf and its default value is 0.

mir_cuts: Frequency (in terms of nodes) for generating MIR cuts in branch-and-cut
If k ¿ 0, cuts are generated every k nodes, if -99 ¡ k ¡ 0 cuts are generated every -k nodes but Cbc may decide to stop generating cuts, if not enough are generated at the root node, if k=-99 generate cuts only at the root node, if k=0 or 100 do not generate cuts. The valid range for this integer option is -100 ≤ mir_cuts < +inf and its default value is -5.

reduce_and_split_cuts: Frequency (in terms of nodes) for generating reduce-and-split cuts in branch-and-cut
If k ¿ 0, cuts are generated every k nodes, if -99 ¡ k ¡ 0 cuts are generated every -k nodes but Cbc may decide to stop generating cuts, if not enough are generated at the root node, if k=-99 generate cuts only at the root node, if k=0 or 100 do not generate cuts. The valid range for this integer option is -100 ≤ reduce_and_split_cuts < +inf and its default value is 0.

### MINLP Heuristics

feasibility_pump_objective_norm: Norm of feasibility pump objective function
The valid range for this integer option is 1 ≤ feasibility_pump_objective_norm ≤ 2 and its default value is 1.

heuristic_RINS: if yes runs the RINS heuristic
The default value for this string option is ”no”.
Possible values:

- no: don’t run it
- yes: runs the heuristic

heuristic_dive_MIP_vectorLength: if yes runs the Dive MIP VectorLength heuristic
The default value for this string option is ”no”.
Possible values:

- no: don’t run it
- yes: runs the heuristic

heuristic_dive_fractional: if yes runs the Dive Fractional heuristic
The default value for this string option is ”no”.
Possible values:

- no: don’t run it
- yes: runs the heuristic

heuristic_dive_vectorLength: if yes runs the Dive VectorLength heuristic
The default value for this string option is ”no”.
Possible values:

- no: don’t run it
- yes: runs the heuristic

heuristic_feasibility_pump: whether the heuristic feasibility pump should be used
The default value for this string option is ”no”.
Possible values:

- no: don’t use it
- yes: use it

pump_for_minlp: if yes runs FP for MINLP
The default value for this string option is ”no”.
Possible values:

- no: don’t run it
- yes: runs the heuristic

### MINLP heuristics

heuristic_dive_MIP_fractional: if yes runs the Dive MIP Fractional heuristic
The default value for this string option is ”no”.
Possible values:

- no: don’t run it
- yes: runs the heuristic

### Nlp solution robustness

max_consecutive_failures: (temporarily removed) Number n of consecutive unsolved problems before aborting a branch of the tree.
When n > 0, continue exploring a branch of the tree until n consecutive problems in the branch are unsolved (we call unsolved a problem for which Ipopt can not guarantee optimality within the specified tolerances). The valid range for this integer option is 0 ≤ max_consecutive_failures < +inf and its default value is 10.

max_random_point_radius: Set max value r for coordinate of a random point.
When picking a random point coordinate i will be in the interval [min(max(l,-r),u-r), max(min(u,r),l+r)] (where l is the lower bound for the variable and u is its upper bound) The valid range for this real option is 0 < max_random_point_radius < +inf and its default value is 100000.

num_iterations_suspect: Number of iterations over which a node is considered ”suspect” (for debugging purposes only, see detailed documentation).
When the number of iterations to solve a node is above this number, the subproblem at this node is considered to be suspect and it will be outputed in a file (set to -1 to deactivate this). The valid range for this integer option is -1 ≤ num_iterations_suspect < +inf and its default value is -1.

num_retry_unsolved_random_point: Number k of times that the algorithm will try to resolve an unsolved NLP with a random starting point (we call unsolved an NLP for which Ipopt is not able to guarantee optimality within the specified tolerances).
When Ipopt fails to solve a continuous NLP sub-problem, if k > 0, the algorithm will try again to solve the failed NLP with k new randomly chosen starting points or until the problem is solved with success. The valid range for this integer option is 0 ≤ num_retry_unsolved_random_point < +inf and its default value is 0.

random_point_perturbation_interval: Amount by which starting point is perturbed when choosing to pick random point by perturbating starting point
The valid range for this real option is 0 < random_point_perturbation_interval < +inf and its default value is 1.

random_point_type: method to choose a random starting point
The default value for this string option is ”Jon”.
Possible values:

- Jon: Choose random point uniformly between the bounds
- Andreas: perturb the starting point of the problem within a prescribed interval
- Claudia: perturb the starting point using the perturbation radius suffix information

### Nlp solve options in B-Hyb

nlp_solve_frequency: Specify the frequency (in terms of nodes) at which NLP relaxations are solved in B-Hyb.
A frequency of 0 amounts to to never solve the NLP relaxation. The valid range for this integer option is 0 ≤ nlp_solve_frequency < +inf and its default value is 10.

nlp_solve_max_depth: Set maximum depth in the tree at which NLP relaxations are solved in B-Hyb.
A depth of 0 amounts to to never solve the NLP relaxation. The valid range for this integer option is 0 ≤ nlp_solve_max_depth < +inf and its default value is 10.

nlp_solves_per_depth: Set average number of nodes in the tree at which NLP relaxations are solved in B-Hyb for each depth.
The valid range for this real option is 0 ≤ nlp_solves_per_depth < +inf and its default value is 1 ⋅ 10+100.

### Options for MILP solver

milp_log_level: specify MILP solver log level.
Set the level of output of the MILP subsolver in OA : 0 - none, 1 - minimal, 2 - normal low, 3 - normal high The valid range for this integer option is 0 ≤ milp_log_level ≤ 3 and its default value is 0.

milp_solver: Choose the subsolver to solve MILP sub-problems in OA decompositions.
To use Cplex, a valid license is required and you should have compiled OsiCpx in COIN-OR (see Osi documentation). The default value for this string option is ”Cbc_D”.
Possible values:

- Cbc_D: Coin Branch and Cut with its default
- Cbc_Par: Coin Branch and Cut with passed parameters
- Cplex: Ilog Cplex

### Options for OA decomposition

oa_decomposition: If yes do initial OA decomposition
The default value for this string option is ”no”.
Possible values:

- no:
- yes:

oa_log_frequency: display an update on lower and upper bounds in OA every n seconds
The valid range for this real option is 0 < oa_log_frequency < +inf and its default value is 100.

oa_log_level: specify OA iterations log level.
Set the level of output of OA decomposition solver : 0 - none, 1 - normal, 2 - verbose The valid range for this integer option is 0 ≤ oa_log_level ≤ 2 and its default value is 1.

### Options for ecp cuts generation

ecp_abs_tol: Set the absolute termination tolerance for ECP rounds.
The valid range for this real option is 0 ≤ ecp_abs_tol < +inf and its default value is 1 ⋅ 10-06.

ecp_max_rounds: Set the maximal number of rounds of ECP cuts.
The valid range for this integer option is 0 ≤ ecp_max_rounds < +inf and its default value is 5.

ecp_propability_factor: Factor appearing in formula for skipping ECP cuts.
Choosing -1 disables the skipping. The valid range for this real option is -inf < ecp_propability_factor < +inf and its default value is 10.

ecp_rel_tol: Set the relative termination tolerance for ECP rounds.
The valid range for this real option is 0 ≤ ecp_rel_tol < +inf and its default value is 0.

filmint_ecp_cuts: Specify the frequency (in terms of nodes) at which some a la filmint ecp cuts are generated.
A frequency of 0 amounts to to never solve the NLP relaxation. The valid range for this integer option is 0 ≤ filmint_ecp_cuts < +inf and its default value is 0.

### Options for feasibility checker using OA cuts

feas_check_cut_types: Choose the type of cuts generated when an integer feasible solution is found
If it seems too much memory is used should try Benders to use less The default value for this string option is ”outer-approximations”.
Possible values:

- outer-approximations: Generate a set of Outer Approximations cuts.
- Benders: Generate a single Benders cut.

feas_check_discard_policy: How cuts from feasibility checker are discarded
Normally to avoid cycle cuts from feasibility checker should not be discarded in the node where they are generated. However Cbc sometimes does it if no care is taken which can lead to an infinite loop in Bonmin (usualy on simple problems). To avoid this one can instruct Cbc to never discard a cut but if we do that for all cuts it can lead to memory problems. The default policy here is to detect cycles and only then impose to Cbc to keep the cut. The two other alternative are to instruct Cbc to keep all cuts or to just ignore the problem and hope for the best The default value for this string option is ”detect-cycles”.
Possible values:

- detect-cycles: Detect if a cycle occurs and only in this case force not to discard.
- keep-all: Force cuts from feasibility checker not to be discarded (memory hungry but sometimes better).
- treated-as-normal: Cuts from memory checker can be discarded as any other cuts (code may cycle then)

generate_benders_after_so_many_oa: Specify that after so many oa cuts have been generated Benders cuts should be generated instead.
It seems that sometimes generating too many oa cuts slows down the optimization compared to Benders due to the size of the LP. With this option we specify that after so many OA cuts have been generated we should switch to Benders cuts. The valid range for this integer option is 0 ≤ generate_benders_after_so_many_oa < +inf and its default value is 5000.

### Options for feasibility pump

fp_log_frequency: display an update on lower and upper bounds in FP every n seconds
The valid range for this real option is 0 < fp_log_frequency < +inf and its default value is 100.

fp_log_level: specify FP iterations log level.
Set the level of output of OA decomposition solver : 0 - none, 1 - normal, 2 - verbose The valid range for this integer option is 0 ≤ fp_log_level ≤ 2 and its default value is 1.

### Options for non-convex problems

coeff_var_threshold: Coefficient of variation threshold (for dynamic definition of cutoff_decr).
Coefficient of variation threshold (for dynamic definition of cutoff_decr). The valid range for this real option is 0 ≤ coeff_var_threshold < +inf and its default value is 0.1.

dynamic_def_cutoff_decr: Do you want to define the parameter cutoff_decr dynamically?
The default value for this string option is ”no”.
Possible values:

- no: No, define it statically
- yes: Yes, define it dynamically

first_perc_for_cutoff_decr: The percentage used when, the coeff of variance is smaller than the threshold, to compute the cutoff_decr dynamically.
The percentage used when, the coeff of variance is smaller than the threshold, to compute the cutoff_decr dynamically. The valid range for this real option is -inf < first_perc_for_cutoff_decr < +inf and its default value is -0.02.

max_consecutive_infeasible: Number of consecutive infeasible subproblems before aborting a branch.
Will continue exploring a branch of the tree until ”max_consecutive_infeasible”consecutive problems are infeasibles by the NLP sub-solver. The valid range for this integer option is 0 ≤ max_consecutive_infeasible < +inf and its default value is 0.

num_resolve_at_infeasibles: Number k of tries to resolve an infeasible node (other than the root) of the tree with different starting point.
The algorithm will solve all the infeasible nodes with k different random starting points and will keep the best local optimum found. The valid range for this integer option is 0 ≤ num_resolve_at_infeasibles < +inf and its default value is 0.

num_resolve_at_node: Number k of tries to resolve a node (other than the root) of the tree with different starting point.
The algorithm will solve all the nodes with k different random starting points and will keep the best local optimum found. The valid range for this integer option is 0 ≤ num_resolve_at_node < +inf and its default value is 0.

num_resolve_at_root: Number k of tries to resolve the root node with different starting points.
The algorithm will solve the root node with k random starting points and will keep the best local optimum found. The valid range for this integer option is 0 ≤ num_resolve_at_root < +inf and its default value is 0.

second_perc_for_cutoff_decr: The percentage used when, the coeff of variance is greater than the threshold, to compute the cutoff_decr dynamically.
The percentage used when, the coeff of variance is greater than the threshold, to compute the cutoff_decr dynamically. The valid range for this real option is -inf < second_perc_for_cutoff_decr < +inf and its default value is -0.05.

### Outer Approximation cuts generation

add_only_violated_oa: Do we add all OA cuts or only the ones violated by current point?
The default value for this string option is ”no”.
Possible values:

- no: Add all cuts
- yes: Add only violated Cuts

oa_cuts_log_level: level of log when generating OA cuts.
0: outputs nothing, 1: when a cut is generated, its violation and index of row from which it originates, 2: always output violation of the cut. 3: output generated cuts incidence vectors. The valid range for this integer option is 0 ≤ oa_cuts_log_level < +inf and its default value is 0.

oa_cuts_scope: Specify if OA cuts added are to be set globally or locally valid
The default value for this string option is ”global”.
Possible values:

- local: Cuts are treated as globally valid
- global: Cuts are treated as locally valid

tiny_element: Value for tiny element in OA cut
We will remove ”cleanly” (by relaxing cut) an element lower than this. The valid range for this real option is -0 ≤ tiny_element < +inf and its default value is 1 ⋅ 10-08.

very_tiny_element: Value for very tiny element in OA cut
Algorithm will take the risk of neglecting an element lower than this. The valid range for this real option is -0 ≤ very_tiny_element < +inf and its default value is 1 ⋅ 10-17.

### Output ond log-levels options

bb_log_interval: Interval at which node level output is printed.
Set the interval (in terms of number of nodes) at which a log on node resolutions (consisting of lower and upper bounds) is given. The valid range for this integer option is 0 ≤ bb_log_interval < +inf and its default value is 100.

bb_log_level: specify main branch-and-bound log level.
Set the level of output of the branch-and-bound : 0 - none, 1 - minimal, 2 - normal low, 3 - normal high The valid range for this integer option is 0 ≤ bb_log_level ≤ 5 and its default value is 1.

lp_log_level: specify LP log level.
Set the level of output of the linear programming sub-solver in B-Hyb or B-QG : 0 - none, 1 - minimal, 2 - normal low, 3 - normal high, 4 - verbose The valid range for this integer option is 0 ≤ lp_log_level ≤ 4 and its default value is 0.

nlp_log_at_root: Specify a different log level for root relaxtion.
The valid range for this integer option is 0 ≤ nlp_log_at_root ≤ 12 and its default value is 0.

### Strong branching setup

candidate_sort_criterion: Choice of the criterion to choose candidates in strong-branching
The default value for this string option is ”best-ps-cost”.
Possible values:

- best-ps-cost: Sort by decreasing pseudo-cost
- worst-ps-cost: Sort by increasing pseudo-cost
- most-fractional: Sort by decreasing integer infeasibility
- least-fractional: Sort by increasing integer infeasibility

maxmin_crit_have_sol: Weight towards minimum in of lower and upper branching estimates when a solution has been found.
The valid range for this real option is 0 ≤ maxmin_crit_have_sol ≤ 1 and its default value is 0.1.

maxmin_crit_no_sol: Weight towards minimum in of lower and upper branching estimates when no solution has been found yet.
The valid range for this real option is 0 ≤ maxmin_crit_no_sol ≤ 1 and its default value is 0.7.

min_number_strong_branch: Sets minimum number of variables for strong branching (overriding trust)
The valid range for this integer option is 0 ≤ min_number_strong_branch < +inf and its default value is 0.

number_before_trust_list: Set the number of branches on a variable before its pseudo costs are to be believed during setup of strong branching candidate list.
The default value is that of ”number_before_trust” The valid range for this integer option is -1 ≤ number_before_trust_list < +inf and its default value is 0.

number_look_ahead: Sets limit of look-ahead strong-branching trials
The valid range for this integer option is 0 ≤ number_look_ahead < +inf and its default value is 0.

number_strong_branch_root: Maximum number of variables considered for strong branching in root node.
The valid range for this integer option is 0 ≤ number_strong_branch_root < +inf and its default value is 2147483647.

setup_pseudo_frac: Proportion of strong branching list that has to be taken from most-integer-infeasible list.
The valid range for this real option is 0 ≤ setup_pseudo_frac ≤ 1 and its default value is 0.5.

trust_strong_branching_for_pseudo_cost: Whether or not to trust strong branching results for updating pseudo costs.
The default value for this string option is ”yes”.
Possible values:

- no:
- yes:

### nlp interface option

file_solution: Write a file bonmin.sol with the solution
The default value for this string option is ”no”.
Possible values:

- yes:
- no:

nlp_log_level: specify NLP solver interface log level (independent from ipopt print_level).
Set the level of output of the OsiTMINLPInterface : 0 - none, 1 - normal, 2 - verbose The valid range for this integer option is 0 ≤ nlp_log_level ≤ 2 and its default value is 1.

nlp_solver: Choice of the solver for local optima of continuous nlp’s
Note that option will work only if the specified solver has been installed. Ipopt will usualy be installed with Bonmin by default. For FilterSQP please see http://www-unix.mcs.anl.gov/ leyffer/solvers.html on how to obtain it and https://projects.coin-or.org/Bonmin/wiki/HintTric- ks on how to configure Bonmin to use it. The default value for this string option is ”Ipopt”.
Possible values:

- Ipopt: Interior Point OPTimizer (https://projects.coin-or.org/Ipopt)
- filterSQP: Sequential quadratic programming trust region algorithm (http://www-unix.mcs.anl.gov/ leyffer/solvers.h- tml)
- all: run all available solvers at each node

warm_start: Select the warm start method
This will affect the function getWarmStart(), and as a consequence the warm starting in the various algorithms. The default value for this string option is ”none”.
Possible values:

- none: No warm start
- optimum: Warm start with direct parent optimum
- interior_point: Warm start with an interior point of direct parent