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Enhancements in SAS/OR® 14.1 Software

Overview

SAS/OR 14.1 adds a number of new optimization capabilities that shorten optimization time, increase diagnostic capabilities, and make the software easier to use. Highlights include the following:

SAS Simulation Studio 14.1, a component of SAS/OR 14.1 for Windows environments, adds features that improve the accuracy of your models and give you additional controls on model execution. Highlights include the following:

Mathematical Optimization Updates

Solver Performance Improvements

Several optimization solvers have improved their performance over that of SAS/OR 13.2 as follows:

PROC OPTMODEL Improvements

The OPTMODEL procedure makes three major changes:

Other Optimization and Related Improvements

PROC CLP adds the new conflict-directed variable selection strategies, VARSELECT=WDEG and VARSELECT=DOMWDEG; adds a new dynamic variable section strategy, VARSELECT=DOMDDEG; and promotes the PACK and LEXICO constraint classes to production status.

PROC OPTNET enables faster graph data input. The STANDARDIZED_LABELS option in the PROC OPTNET statement enables you to read graph data that contain only numeric node identifiers more quickly. More generally, PROC OPTNET supports parallel computing, including parallel graph data input. This is especially helpful in shortening the time that is needed to input large-scale graph data. You can use the PERFORMANCE statement and its NTHREADS= option to request multithreaded computing.

PROC OPTNET adds enhancements to three of the algorithms that it uses. The TSP (traveling salesman problem) algorithm can solve asymmetric problems, which are defined on directed graphs; the shortest path algorithm can accept negative link weights; and the default connected components algorithm for undirected graphs is the more efficient union-find algorithm.

PROC OPTNET produces ODS tables as output. You can use the DETAILS option in the PERFORMANCE statement to request that PROC OPTNET produce the Timing ODS table, which reports the amount of time that each step of the procedure uses.

The NLP solver and the quadratic programming (QP) solver each add the IIS= option, which directs the solver to identify an irreducible infeasible set among the linear constraints and decision variable bounds for a problem that is found to be infeasible. Identification of irreducible infeasible sets provides valuable guidance in restoring infeasible problems to feasibility.

The MILP solver now runs in parallel (threaded) mode by default for improved performance.

The DECOMP algorithm for the LP and MILP solvers adds the SET value for the METHOD= option. This value directs the DECOMP algorithm to find a set-partitioning or set-covering structure in the constraint matrix. If such constraints are detected, they serve as the linking constraints, and the remaining weakly connected components of the constraint matrix define blocks of constraints for use in the DECOMP algorithm.

Discrete-Event Simulation Updates

SAS Simulation Studio 14.1, which provides a graphical environment for building and working with discrete-event simulation models, makes four major improvements:

For More Information

SAS/OR 14.1 is now available. For complete information about all SAS/OR releases, see the documentation at support.sas.com/stat/.

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