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 or distributed) mode by default for improved performance. Note: Distributed mode requires SAS High-Performance Optimization.
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.