The OPTLP Procedure
- Overview
- Getting Started
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Syntax
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DetailsData Input and OutputPresolvePricing Strategies for the Primal and Dual Simplex AlgorithmsWarm Start for the Primal and Dual Simplex AlgorithmsThe Network Simplex AlgorithmThe Interior Point AlgorithmIteration Log for the Primal and Dual Simplex AlgorithmsIteration Log for the Network Simplex AlgorithmIteration Log for the Interior Point AlgorithmIteration Log for the Crossover AlgorithmConcurrent LPParallel ProcessingODS TablesIrreducible Infeasible SetMacro Variable _OROPTLP_
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Examples
- References
For a linear programming problem, an irreducible infeasible set (IIS) is an infeasible subset of constraints and variable bounds that will become feasible if any single constraint or variable bound is removed. It is possible to have more than one IIS in an infeasible LP. Identifying an IIS can help isolate the structural infeasibility in an LP.
The presolver in the OPTLP procedure can detect infeasibility, but it identifies only the variable bound or constraint that triggers the infeasibility.
The IIS= ON option directs the OPTLP procedure to search for an IIS in a specified LP. The OPTLP procedure does not apply the presolver to the problem during the IIS search. If PROC OPTLP detects an IIS, it first outputs the IIS to the data sets that are specified by the PRIMALOUT= and DUALOUT= options, and then it stops. The number of iterations that are reported in the macro variable and the ODS table is the total number of simplex iterations. This total includes the initial LP solve and all subsequent iterations during the constraint deletion phase.
The IIS= option can add special values to the _STATUS_ variables in the output data sets. (For more information, see the section
Data Input and Output.) For constraints, a status of "I_L", "I_U", or "I_F" indicates that the "GE" (
), "LE" (
), or "EQ" (=) constraint, respectively, is part of the IIS. For range constraints, a status of "I_L" or "I_U" indicates that
the lower or upper bound of the constraint, respectively, is needed for the IIS, and "I_F" indicates that the bounds in the
constraint are conflicting. For variables, a status of "I_L", "I_U", or "I_F" indicates that the lower, upper, or both bounds
of the variable, respectively, are needed for the IIS. From this information, you can identify both the names of the constraints
(variables) in the IIS and the corresponding bound where infeasibility occurs.
Making any one of the constraints or variable bounds in the IIS nonbinding removes the infeasibility from the IIS. In some
cases, changing a right-hand side or bound by a finite amount removes the infeasibility. However, the only way to guarantee
removal of the infeasibility is to set the appropriate right-hand side or bound to 
or 
. Because it is possible for an LP to have multiple irreducible infeasible sets, simply removing the infeasibility from one
set might not make the entire problem feasible. To make the entire problem feasible, you can specify IIS=ON and rerun PROC
OPTLP after removing the infeasibility from an IIS. Repeating this process until the LP solver no longer detects an IIS results
in a feasible problem. This approach to infeasibility repair can produce different end problems depending on which right-hand
sides and bounds you choose to relax.
Changing different constraints and bounds can require considerably different changes to the MPS-format SAS data set. For example,
if you use the default lower bound of 0 for a variable but you want to relax the lower bound to , you might need to add an MI row to the BOUNDS section of the data set. For more information about changing variable and
constraint bounds, see Chapter 17: The MPS-Format SAS Data Set.
The IIS= option in PROC OPTLP uses two different methods to identify an IIS:
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Based on the result of the initial solve, the sensitivity filter removes several constraints and variable bounds immediately while still maintaining infeasibility. This phase is quick and dramatically reduces the size of the IIS.
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Next, the deletion filter removes each remaining constraint and variable bound one by one to check which of them are needed to obtain an infeasible system. This second phase is more time consuming, but it ensures that the IIS set that PROC OPTLP returns is indeed irreducible. The progress of the deletion filter is reported at regular intervals. Occasionally, the sensitivity filter might be called again during the deletion filter to improve performance.
See Example 12.7 for an example that demonstrates the use of the IIS= option in locating and removing infeasibilities. You can find more details about IIS algorithms in Chinneck (2008).