Instructor

Soman S.A.

Semester

Autumn ‘20

Course Difficulty

Easy-Moderate
Since the course is an intro to optimization techniques, the concepts involved are fairly easy to grasp. However, the topics involved can be used to formulate a wide variety of problems so the exams/assignments may include a few tricky problems.

Time Commitment Required

On the lower side
Course just had 1 assignment and an endsem. Can be managed by starting a few days before the deadline/exam

Grading Policy and Statistics

Available on ASC

Attendance Policy

No attendance
All lectures are uploaded on youtube

Pre-requisites

No prereqs, its an intro course

Evaluation Scheme

1 Assignment of 20%
Endsem of 80%

Topics Covered in the Course

1. Introduction: Basic definition, problem formulation and illustrative examples. Existence of minimum, Weierstrass’s Theorem, Necessary conditions for unconstrained minimization, Sufficiency conditions for unconstrained minimization.
2. Convex Analysis: convex sets, closest point theorem, Theorem of alternatives, Farka’s lemma, Gordan’s theorem, convex functions, minima and maxima of convex functions, generalizations.
3. Linear programming: Motivation, formulation, optimality conditions, simplex method, dual formulation and optimality conditions.
4. Constrained minimization: role of constraints, linear and non-linear constraints, equality and inequality constraints, optimality conditions, Fritz John optimality conditions, Karush Kuhn Tucker optimality conditions, necessary conditions and sufficiency conditions.
5. Application of optimization theory: Application to networks and economics.
6. Quadratic programming: formulation, optimality conditions and algorithms, applications. 7. Algorithms for unconstrained minimization: Univariate Line search methods, Multidimensional search methods, steepest descent, Newton’s, Quasi newton and trust region approaches, method of conjugate directions, CG method.

Teaching Style

All lectures available on youtube
Teaching style is easy to understand and pace is easy to follow

Tutorials/Assignments/Projects

Practice problems are given in each lecture
Most of the assignment questions can be solved fairly easily after watching the lectures but there are a few tricky questions which will take significant amount of time to solve.

Feedback on Exams

Most of the exam questions are quite easy, but there are a few tricky problems which will require good understanding of the concepts.

Motivation for taking this course

Optimization techniques are relevant to all engineering fields, so the skills taken from the course would come in handy in the future.

Course Importance

Optimization techniques are relevant to all engineering fields, so the skills taken from the course would come in handy in the future.

How strongly would I recommend this course?

7/10

When to take this course?

5th sem
Can be taken in any sem

Going Forward

After taking this course, advanced courses on optimization techniques would be much easier to grasp. There are quite a few such courses offered by the EE and Syscon depts

Review By: Nandagopal Vidhu