What’s New in SAS/OR 9.2 |
The OPTMODEL procedure provides a modeling environment that is tailored to building, solving, and maintaining optimization models. This makes the process of translating the symbolic formulation of an optimization model into PROC OPTMODEL virtually transparent, since the modeling language mimics the symbolic algebra of the formulation as closely as possible. PROC OPTMODEL also streamlines and simplifies the critical process of populating optimization models with data from SAS data sets. All of this transparency produces models that are more easily inspected for completeness and correctness, more easily corrected, and more easily modified, whether through structural changes or through the substitution of new data for old.
The OPTMODEL procedure comprises the powerful OPTMODEL modeling language and state-of-the-art solvers for several classes of mathematical programming problems.
Seven solvers are available to OPTMODEL as listed in Table 1.1:
Problem |
Solver |
linear programming |
LP |
mixed integer programming |
MILP |
quadratic programming (experimental) |
QP |
nonlinear programming, unconstrained |
NLPU |
general nonlinear programming |
NLPC |
general nonlinear programming |
SQP |
general nonlinear programming (experimental) |
IPNLP |
New in SAS/OR 9.2, the experimental IIS= option for the LP solver enables you to identify, for an infeasible linear program, constraints and variable bounds that form an irreducible infeasible set (IIS). Identifying an IIS can be very helpful in diagnosing and remedying infeasibility in a linear program.
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