Multi-Criteria Decision Making Course | IIT Kanpur | Prof. Raghu Nandan Sengupta
Course Details
| Exam Registration | 23 |
|---|---|
| Course Status | Ongoing |
| Course Type | Elective |
| Language | English |
| Duration | 12 weeks |
| Categories | Multidisciplinary |
| 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 | 19 Apr 2026 IST |
| NCrF Level | 4.5 — 8.0 |
Navigate Complexity with Confidence: A Guide to the Multi-Criteria Decision Making Course
In a world brimming with complex choices—from engineering design and supply chain management to financial portfolios and public policy—how do we make the best decision when multiple, often conflicting, criteria are at play? The answer lies in the rigorous, mathematical framework of Multi-Criteria Decision Making (MCDM). We are thrilled to present a deep-dive, 12-week course on this pivotal subject, designed and delivered by a leading expert from the Indian Institute of Technology Kanpur.
Meet Your Instructor: Prof. Raghu Nandan Sengupta
This course is led by Prof. Raghu Nandan Sengupta, a full Professor in the Industrial & Management Engineering (IME) Department at IIT Kanpur. With a distinguished career since 2003, Prof. Sengupta brings immense academic and administrative expertise to the table.
His research spans Theoretical Statistics, Decision Analysis, Quantitative Finance, and Robust Optimization, with publications in top-tier journals such as the European Journal of Operational Research (EJOR), Quantitative Finance, and Annals of Operations Research. He is also the author of influential books like Decision Sciences: Theory and Practice. Beyond research, his leadership roles as former Head of the IME Department and Vice Chairman for JEE Advanced and GATE/JAM underscore his deep commitment to advanced education. An accomplished teacher, he brings complex topics to life in areas like Management Decision Analysis, Project Management, and Stochastic Processes.
Course Overview: What is Multi-Criteria Decision Making?
MCDM is the science of making optimal choices in the presence of multiple, competing objectives or criteria. It is split into two main branches:
- Multi-Objective Optimization (MOO): Deals with problems where you optimize several objectives simultaneously (e.g., minimizing cost while maximizing durability).
- Multi-Attribute Decision Making (MADM): Focuses on selecting the best alternative from a finite set based on multiple attributes (e.g., choosing a supplier based on cost, quality, and delivery time).
This course is designed to equip you with a rich repertoire of tools to tackle such problems scientifically, moving beyond intuition to mathematically-grounded, rational decision-making.
Who Should Enroll?
This multidisciplinary course is ideal for:
- Bachelor's, Master's, and PhD students in Engineering (all streams), Mathematics, Statistics, Industrial Engineering, Management, and Operations Research.
- Professionals and researchers looking to add formal decision-making frameworks to their skill set.
Prerequisites
- A foundational understanding of statistics and operations research at the BSc/BTech level.
Industry Relevance
The techniques taught are directly applicable in sectors like Automobile, Steel, Cement, Advanced Manufacturing, and Logistics, making this course highly valuable for both academic and corporate advancement.
Your 12-Week Learning Journey
The course is meticulously structured to build your knowledge from foundational theories to advanced applications.
| Week | Key Topics Covered |
|---|---|
| Weeks 1-2 | Choice Theory, Rationality, Utility Theory, Risk, Stochastic Dominance. |
| Weeks 3-5 | Preference Theory, Decision Theory (Normative, Prescriptive, Descriptive), Bayesian Analysis. |
| Weeks 6-8 | Multi-Objective Optimization (MOO): Pareto Principle, Goal Programming, KKT conditions, Vector Optimization. |
| Week 9 | Meta-heuristics for MOO (Genetic Algorithms, Particle Swarm Optimization, etc.). |
| Week 10 | Multi-Attribute Utility/Value Theory (MAUT/MAVT), Outranking methods. |
| Weeks 11-12 | Key MADM Techniques: AHP, ANP, TOPSIS, ELECTRE, VIKOR, PROMETHEE, and more. |
Essential Reading & Resources
The course is supported by a comprehensive reading list, including Prof. Sengupta's own text. Key textbooks include:
- Berger's Statistical Decision Theory and Bayesian Analysis
- Saaty's work on The Logic of Priorities
- Steuer's Multiple Criteria Optimization: Theory, Computation and Application
- Sengupta, Gupta & Dutta's Decision Sciences Theory and Practice
These are complemented by over 20 reference texts covering state-of-the-art surveys and applications across various domains.
Key Takeaways: Why This Course is Essential
By the end of this course, you will:
- Master a Toolkit: Gain proficiency in a wide array of MCDM methods, from classic utility theory to modern meta-heuristics.
- Build Theoretical Rigor: Understand the mathematical foundations that underpin rational decision-making.
- Solve Real Problems: Apply techniques to practical scenarios in engineering, management, finance, and environmental science.
- Enhance Decision Quality: Move from ad-hoc choices to structured, defensible, and optimal decisions in complex environments.
Whether you are a student aiming to excel in your research, a professional seeking to solve operational complexities, or a lifelong learner fascinated by the science of choice, this course offers the knowledge and tools to transform your decision-making capabilities.
Embark on this 12-week journey to master the art and science of making better decisions in a complex world.
Enroll Now →