Computer Aided Applied Single Objective Optimization Course | IIT Guwahati | Prof. Prakash Kotecha
Course Details
| Exam Registration | 19 |
|---|---|
| Course Status | Ongoing |
| Course Type | Elective |
| Language | English |
| Duration | 12 weeks |
| Categories | Multidisciplinary, Computational Chemical Engineering |
| Credit Points | 3 |
| Level | Undergraduate/Postgraduate |
| Start Date | 19 Jan 2026 |
| End Date | 10 Apr 2026 |
| Enrollment Ends | 02 Feb 2026 |
| Exam Registration Ends | 20 Feb 2026 |
| Exam Date | 18 Apr 2026 IST |
| NCrF Level | 4.5 — 8.0 |
Unlock the Power of Optimization: A Deep Dive into IIT Guwahati's Premier Course
In the realms of science, engineering, and business, the quest for the 'best' solution—be it maximum efficiency, minimum cost, or optimal design—is universal. This pursuit is formalized through optimization. If you're a student, researcher, or professional looking to master the tools that drive innovation and efficiency, the course "Computer Aided Applied Single Objective Optimization" from the Indian Institute of Technology Guwahati is your gateway.
Designed and instructed by Prof. Prakash Kotecha, this 12-week multidisciplinary course bridges the gap between complex theoretical concepts and their powerful, practical applications. It equips you with a formidable arsenal of both mathematical and computational intelligence algorithms to tackle challenging combinatorial optimization problems head-on.
Meet Your Instructor: Prof. Prakash Kotecha
The course is led by an expert at the forefront of optimization research. Dr. Prakash Kotecha is an Associate Professor in the Department of Chemical Engineering at IIT Guwahati. With a solid academic foundation—a Bachelors from Pondicherry Engineering College, a Masters from Coimbatore Institute of Technology, and a PhD from IIT Bombay—he specializes in computational intelligence algorithms and their application to combinatorial optimization problems.
His extensive publication record in reputed journals and conferences ensures that the course content is cutting-edge, relevant, and informed by active research. Learning from an instructor of this caliber provides invaluable insights into both the fundamentals and the frontiers of the field.
Who Should Enroll? (Intended Audience & Prerequisites)
This course is meticulously crafted to be accessible and beneficial to a wide audience:
- Students (Undergraduate/Postgraduate): From engineering (chemical, mechanical, civil, computer science) to data science and operations research.
- Researchers & Academia: Looking to strengthen their methodological toolkit for complex problem-solving.
- Working Professionals: In sectors like manufacturing, logistics, finance, pharmaceuticals, and any field where resource allocation and process optimization are key.
Prerequisite: A foundation in Basic Mathematics is all you need to begin this journey. The course is designed to build your knowledge from the ground up.
Why This Course? Key Features & Industry Relevance
This isn't just another theoretical lecture series. Its applied focus sets it apart:
- Hands-On Tool Mastery: Learn to quickly utilize state-of-the-art software tools like MATLAB Optimization Toolbox, GAMS, and IBM ILOG CPLEX Optimization Studio.
- Real-World Case Study: A unique and crucial component where you'll apply learned techniques to a realistic problem, understanding the nuances of problem formulation, solution, and analysis.
- Broad Industry Support: The skills taught are universally applicable. Industries ranging from core engineering and supply chain to finance and artificial intelligence seek professionals proficient in optimization techniques.
Your 12-Week Learning Journey: Course Layout
Here’s a detailed roadmap of what you will learn each week:
| Week | Topic | Focus Area |
|---|---|---|
| 1 | Introduction | Course overview, basics of optimization problems. |
| 2 | Regression | Foundational data modeling technique. |
| 3 | Teaching Learning Based Optimization | A novel population-based algorithm. |
| 4 | Particle Swarm Optimization | Inspired by social behavior of birds/fish. |
| 5 | Differential Evolution | A powerful stochastic optimization method. |
| 6 | Genetic Algorithm | Evolutionary algorithm based on natural selection. |
| 7 | Artificial Bee Colony Optimization | Algorithm inspired by foraging behavior of honey bees. |
| 8 | Constraint Handling & Result Analysis | Managing real-world limits and interpreting solutions. |
| 9 | Linear & Mixed Integer Linear Programming | Classical mathematical optimization techniques. |
| 10 | Case Study Solution | Applying both Mathematical & CI techniques to a realistic problem. |
| 11 | MATLAB Optimization Toolbox | Practical implementation using MATLAB. |
| 12 | GAMS & IBM ILOG Optimization Studio | Introduction to high-level modeling systems for optimization. |
Conclusion: Transform Your Problem-Solving Approach
The "Computer Aided Applied Single Objective Optimization" course is more than a syllabus; it's a comprehensive skill-building program. By its conclusion, you will not only understand the theory behind powerful optimization algorithms but also possess the practical ability to implement them using professional tools to solve complex, real-world problems.
Whether you aim to enhance your academic research, boost your career profile, or simply satiate an intellectual curiosity about optimization, this course offered by IIT Guwahati and Prof. Prakash Kotecha is an exceptional opportunity. Take the first step towards mastering the art and science of optimal decision-making.
Ready to optimize your future? Explore the official NPTEL portal for enrollment details and the next course schedule.
Enroll Now →