This course focuses on linear, nonlinear, and efficiency optimization concepts. Participants learn how to formulate optimization problems and how to make their formulations efficient by using index sets and arrays. The demonstrations in the course include examples of data envelopment analysis and portfolio optimization. The OPTMODEL procedure is used to solve optimization problems that reinforce concepts introduced in the course.
Learn how to
- identify and formulate appropriate approaches to solving various linear and nonlinear optimization problems
- create optimization models commonly used in industry
- formulate and solve a data envelopment analysis
- solve optimization problems using the OPTMODEL procedure in SAS.
Who should attend
Those who want to develop the advanced knowledge and skills necessary to work as a data scientist, especially those with a strong background in applied mathematics
Before enrolling in the data science certification program, you should have completed all coursework for the SAS Certified Big Data Professional program or passed the Big Data Certification exams. Before attending this course, you should have
- completed an undergraduate course in operations research that includes linear programming, 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 course-specific knowledge and skill by completing the SAS Programming 1: Essentials - session2 course.
This course addresses SAS/OR software.
Introduction to Mathematical Optimization
Linear Programming Problems: Basic Ideas
- a simple example
- the OPTMODEL procedure
Nonlinear Programming Problems
- introduction to linear programming
- formulating and solving linear programming problems using the OPTMODEL procedure
- using index sets and arrays in the OPTMODEL procedure
- dual values and reduced costs in the simplex method (self-study)
- applied data envelopment analysis
- reading SAS data sets (self-study)
- introduction to nonlinear programming
- solving nonlinear programming problems using the OPTMODEL procedure