The OPTMILP Procedure 
Functional Summary 
Table 18.1 summarizes the options available for the OPTMILP procedure, classified by function.
Description 
Option 

Data Set Options 

Input data set 

Constraint activities output data set 

Objective sense (maximization or minimization) 

Primal solution input data set (warm start) 

Primal solution output data set 

Presolve Option 

Type of presolve 

Control Options 

Stopping criterion based on absolute objective gap 

Cutoff value for node removal 

Emphasize feasibility or optimality 

Maximum allowed difference between an integer variable’s value and an integer 

Maximum number of nodes to be processed 

Maximum number of solutions to be found 

Maximum solution time 

Frequency of printing node log 

Toggle ODS output 

Detail of solution progress printed in log 

Probing level 

Stopping criterion based on relative objective gap 

Scale the problem matrix 

Stopping criterion based on target objective value 

Use CPU/real time 

Heuristics Option 

Primal heuristics level 

Search Options 

Node selection strategy 

Use of variable priorities 

Number of simplex iterations performed on each variable in strong branching strategy 

Number of candidates for strong branching 

Rule for selecting branching variable 

Cut Options 

Overall cut level 

Clique cut level 

Flow cover cut level 

Flow path cut level 

Gomory cut level 

Generalized upper bound (GUB) cover cut level 

Implied bounds cut level 

Knapsack cover cut level 

Liftandproject cut level 

Mixed integer rounding (MIR) cut level 

Row multiplier factor for cuts 
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