Building and Solving Optimisation Models with SAS/OR - OROP92
This course focuses on formulating and solving mathematical optimisation using the OPTMODEL procedure, from inputting data to interpreting output and generating reports. The course covers linear, integer, mixed-integer, and nonlinear programming problems, with an emphasis on model formulation and construction.
|3 days - Classroom|
Learn how to
- formulate and solve linear programming problems using the OPTMODEL procedure
- solve integer and mixed-integer programming problems using the OPTMODEL procedure
- solve nonlinear programming problems using the OPTMODEL procedure.
Who should attend?
Anyone who wants to formulate and solve linear, integer, mixed-integer, or nonlinear problems using SAS/OR software
Before attending this course, you should
- have completed an undergraduate course in operations research that includes linear programming or have recent experience using linear programming or be comfortable with matrix algebra.
- be able to execute SAS programs and create SAS data sets. You can gain this experience by completing the SAS Programming 1: Essentials course.
Introduction to Mathematical Optimisation
- overview of mathematical optimisation
- simple examples
- the OPTMODEL procedure
Linear Programming Problems: Basic Ideas
- introduction to linear programming
- formulating and solving linear programming problems using the OPTMODEL procedure
- reading data from SAS data sets
- writing output from the OPTMODEL procedure
- dual values, reduced costs, and pricing in the simplex method
Linear Programming Problems: Additional Topics
- basic control flow and operators in the OPTMODEL procedure
- model updates in the OPTMODEL procedure
- sensitivity analysis and parametric programming (self-study)
- network flow models
Integer and Mixed-Integer Linear Programming Problems
- introduction to integer and mixed-integer linear programming
- solving integer and mixed-integer programming problems using the OPTMODEL procedure
- modeling using binary variables
- modeling Tentaizu as an ILP (self-study)
- mixed-integer linear programming solver options (self-study)
Nonlinear Programming Problems
- introduction to nonlinear programming
- solving nonlinear programming problems using the OPTMODEL procedure
- nonlinear optimisation methods in the OPTMODEL procedure
- additional examples (self-study)
- the NLP procedure and OPTMODEL procedure (self-study)
- reading and creating data
- delimiters and OPTMODEL procedure syntax
- variable, constraints, objectives, and parameters
This course addresses the following software product(s): SAS/OR.