Optimization Basics
This course introduces students to optimization techniques. The course exposes students to basic concepts about the implementation of numerical optimization techniques, assuming that the student does or does not have any kind of idea on these topics. The approach used for teaching this optimization course is based on students having a basic understanding of optimization problem formulations, the important aspects of various optimization algorithms, also about the knowledge of how to use programming to solve optimization problems. The lectures in this course cover Graphical Approaches for Optimization Problems, Notations and Classification of Optimization, Unconstrained Optimization, and Constrained Optimization. Various algorithms such as Golden Section, Gradient Descent, Newton's Methods, Augmented Lagrangian, and Sequential Quadratic Programming (SQP).
Course Lessons
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Course Instructor
Rahul Rai
Dean's Distinguished Professor at Clemson University
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