Multi-Criteria Decision Making and Applications

By Prof. Raghu Nandan Sengupta | IIT Kanpur

Learners enrolled: 174 | Exam registration: 23

ABOUT THE COURSE:

Objective:

In all domain of multiple levels decision making considering numerous alternative and conflicting criterion, it becomes imperative for the decision maker (DM)/set of decision makers (DMs) to come up with the best solution. Ideas of Multi Criteria decision making (MCDM) (comprising of multi objective optimization (MOO) and multi attributive decision making (MADM)) help DMs to make rational as well mathematical well grounded decision to solve these set of problems. In many cases when stakes are high and one has non-commensurable units of measurement as well multiple conflicting objectives, MCDM definitely aids better decision making. This course will benefit students in their masters and doctoral programs and working in a variety of areas like engineering (electrical, mechanical, civil, chemical, etc.), mathematics & statistics (Multiple Bayesian Decision making), economics, management (SCM, quantitative finance, etc.) to tackle and solve interesting problems both from theoretical as well as practical view points.

Key learning take away:

Will help students master the rich repertoire of tools for scientifically/rationally multi criteria decision making.

Will facilitate students with both the basic and advanced theoretical background in MCDM.

Will equip learners with the requisite skills in utilizing different techniques through practical applications.

Will help improve decision-making in myriad of decision process be it engineering, management science, psychology, biological sciences, environment, etc.

INTENDED AUDIENCE: Bachelors, Masters and PhD students from Engineering, Mathematics, IE, Management, Operations Research, etc.

PREREQUISITES:

1. BTech/BSc Statistics

2. BTech/BSc Operations Research

INDUSTRY SUPPORT:

1. Automobile

2. Steel

3. Cement

4. Manufacturing and Advanced Manufacturing

5. Logistics in all fields of industry as well as services

Summary

Course Status :	Ongoing
Course Type :	Elective
Language for course content :	English
Duration :	12 weeks
Category :	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

Note: This exam date is subject to change based on seat availability. You can check final exam date on your hall ticket.

Page Visits

Course layout

Week 1: Choice Theory, Ideas about Rational and Irrational Choice Theory

Week 2: Utility Theory, Concept of Non-satiation, Risk Characteristics, Expected Utility, Risk, Certainty Value, Different Types of Utility functions, Stochastic Dominance (First Order Stochastic Dominance (FOSD), Second Order Stochastic Dominance (SOSD), Third Order Stochastic Dominance (TOSD)), Loss Functions(Cont)

Week 3: Utility Theory, Concept of Non-satiation, Risk Characteristics, Expected Utility, Risk, Certainty Value, Different Types of Utility functions, Stochastic Dominance (First Order Stochastic Dominance (FOSD), Second Order Stochastic Dominance (SOSD), Third Order Stochastic Dominance (TOSD)), Loss Functions

Week 4: Preference Theory, Consumer choice behaviour, Convex and Concave preferences, Comparison of Utility Theory with Preference Theory, Scale of Measurement, Decision Theory, Normative, Prescriptive and Descriptive decisions, Choice under uncertainty, Complex Decisions, Heuristics, Ideas of Bayesian Analysis(Cont)

Week 5: Preference Theory, Consumer choice behaviour, Convex and Concave preferences, Comparison of Utility Theory with Preference Theory, Scale of Measurement, Decision Theory, Normative, Prescriptive and Descriptive decisions, Choice under uncertainty, Complex Decisions, Heuristics, Ideas of Bayesian Analysis

Week 6: Concepts of Multi-Objective Optimization Method (MOOM), Lagrange multiplier, Karush–Kuhn–Tucker (KKT) conditions, Concept of Dominated and Non-dominated Solutions, Ideas of Pareto Principle, Goal Programming, No-preference methods, Priori methods, Scalarizing, Posteriori methods, Concurrent computing, Vector Optimization(Cont)

Week 7: Concepts of Multi-Objective Optimization Method (MOOM), Lagrange multiplier, Karush–Kuhn–Tucker (KKT) conditions, Concept of Dominated and Non-dominated Solutions, Ideas of Pareto Principle, Goal Programming, No-preference methods, Priori methods, Scalarizing, Posteriori methods, Concurrent computing, Vector Optimization(Cont)

Week 8: Concepts of Multi-Objective Optimization Method (MOOM), Lagrange multiplier, Karush–Kuhn–Tucker (KKT) conditions, Concept of Dominated and Non-dominated Solutions, Ideas of Pareto Principle, Goal Programming, No-preference methods, Priori methods, Scalarizing, Posteriori methods, Concurrent computing, Vector Optimization

Week 9: Ideas about Meta-heuristics to solve MOOM like GA, ACO, TS, AIS, PSO, etc.

Week 10: Basic ideas about Multi-Attribute Utility Theory (MAUT) and Multi-Attribute Value Theory (MAVT), Concept of Out ranking methods

Week 11: Weight Sum Method (WSM), Weight Product Method (WPM), Analytical Network Process (ANP), Analytical Hierarchy Process (AHP), ÉLimination et Choix Traduisant la REalité (ELimination Et Choice Translating REality) (ELECTRE), Technique for Order of Preference by Similarity to Ideal Solution (TOPSIS), VIseKriterijumska Optimizacija I Kompromisno Resenje (VIKOR), Preference Ranking Organization METHod for Enrichment of Evaluations (PROMETHEE), Measuring Attractiveness by a Categorical Based Evaluation TecHnique (MACBETH), Potentially All Pairwise RanKings of all possible Alternatives (PAPRIKA), etc.(Cont)

Week 12: Weight Sum Method (WSM), Weight Product Method (WPM), Analytical Network Process (ANP), Analytical Hierarchy Process (AHP), ÉLimination et Choix Traduisant la REalité (ELimination Et Choice Translating REality) (ELECTRE), Technique for Order of Preference by Similarity to Ideal Solution (TOPSIS), VIseKriterijumska Optimizacija I Kompromisno Resenje (VIKOR), Preference Ranking Organization METHod for Enrichment of Evaluations (PROMETHEE), Measuring Attractiveness by a Categorical Based Evaluation TecHnique (MACBETH), Potentially All Pairwise RanKings of all possible Alternatives (PAPRIKA), etc.

Books and references

Text books:

01) James O. Berger, Statistical Decision Theory and Bayesian Analysis, 1985, Springer, ISBN: 978-1-4757-4286-2.

02) Peter C. Fishburn, The Foundations of Expected Utility, Springer, 1982, ISBN (13): 978-94-017-3329-8.

03) Thomas L. Saaty, Luis G. Vargas and Kevin P. Kearns, The Logic of Priorities: Analytical Planning: The Organization of Systems, RWS Publications, 1991, ISBN (13): 978-1888603071.

04) R. Steuer, Multiple Criteria Optimization: Theory, Computation and Application, John Wiley & Sons, 1985, ISBN (10): 047188846X/ISBN (13): 978-0-471-88846-8.

05) Zilany, Milan, Multi Criteria Decision Making, McGraw Hill Book Company, 1982, ISBN (10): 0-07-072795-3.

References:

01) Alireza Alinezhad and Javad Khalili, New Methods and Applications in Multiple Attribute Decision Making (MADM), International Series in Operations Research & Management Science (Vol 277), Springer, 2019, ISBN (13): 978-3-030-15008-2.

02) Vira Chankong, Vira and Yacov Y. Haimes, Multiobjective Decision Making: Theory and Methodology, Elsevier, 1983, ISBN (13): 978-0444007100.

03) Valerie Belton and Theodor J. Stewart, Multiple Criteria Decision Analysis: An Integrated Approach, Springer, 2002, ISBN (13): 978-1-4615-1495-4.

04) Kalyanmoy Deb, Multi-Objective Optimization using Evolutionary Algorithms, Wiley, 2010, ISBN (13): 978-8126528042.

05) Matthias Ehrgott, Multicriteria Optimization, Springer, 2005, ISBN (10): 3-540-21398-8.

06) José R. Figueira, Salvatore Greco and Matthias Ehrogott, Multiple Criteria Decision Analysis: State of the Art Surveys, Springer, 2005, ISBN (10): 0-387-23067-X.

07) Salvatore Greco, Matthias Ehrgott and José Rui Figueira, Trends in Multiple Criteria Decision Analysis (International Series in Operations Research & Management Science: Vol 142), Springer, 2010, ISBN (13): 978-1441959034.

08) Ching-Lai Hwang and Abu Syed Md. Masud, Multiple Objective Decision Making – Methods and Applications, Vol-164 of Lecture Notes in Economics and Mathematical Systems, Springer Verlag, 1979, ISBN (13): 978-3-642-45511-7.

09) Ching-Lai Hwang and Kwangsun Yoon, Multiple Attribute Decision Making Methods and Applications A State-of-the-Art Survey, Springer Verlag, 1981, ISBN (13): 978-3-540-10558-9.

10) Jahn Johannes, Vector Optimization – Theory, Applications, and Extensions, Springer Verlag, 2004, ISBN (13): 978-3-642-17005-8.

11) Ignacy Kaliszewski, Janusz Miroforidis and Dmitry Podkopaev, Multiple Criteria Decision Making by Multiobjective Optimization A Toolbox, Springer, 2016, ISBN (13): 9783319327556.

12) R. Keeney and H. Raiffa, Decisions with Multiple Objectives: Preferences and Tradeoffs, Cambridge University Press, 1993, ISBN (10): 0-52-144185-4.

13) F. H. Knight, Risk, Uncertainty and Profit, Houghton Mifflin Company, 1921.

14) Michal Mankowski and Mikhail Moshkov, Dynamic Programming Multi-Objective Combinatorial Optimization, Springer, 2021, ISBN (13): 978-3030639198.

>15) Kaisa Miettinen, Nonlinear Multiobjective Optimization,Vol-12 of International Series in Operations Research and Management Science, Kluwer, 1999, ISBN (13): 978-1-461-55563-6.

16) Panos M. Pardalos, Antanas Žilinskas and Julius Žilinskas, , Non-Convex Multi-Objective Optimization, Springer, 2017, ISBN (13): 978-3-319-86981-0.

17) B. Roy, Multicriteria Methodology for Decision Aiding, Vol-12 of Nonconvex Optimization and its Applications, Kluwer, 1996, ISBN (13): 978-1-475-72500-1.

18) Y. Sawaragi, H. Nakayama and T. Tanino, Theory of Multiobjective Optimization, Academic Press, 1985, ISBN (10): 0-12-620370-9.

19) Raghu N. Sengupta, A. Gupta and J. Dutta, Decision Sciences Theory and Practice, CRC & Taylor Francis, 2020, ISBN (13): 9780367574376.

20) Evangelos Triantaphyllou, Multi-Criteria Decision Making Methods: A Comparative Study (Applied Optimization Volume 44), Kluwer Academic Publishers, 2000, ISBN: 0-7923-6607-7.

21) Gwo-Hshiung Tzeng and Jih-Jeng Huang, Multiple Attribute Decision Making: Methods and Applications, CRC Press, 2011, ISBN (10): 1439861587/ISBN (13): 978-1-439-86158-5.

22) P. Vincke, Multicriteria Decision Aid, John Wiley & Sons, 1992, ISBN (13): 978-0-471-93184-3.

23) von Neumann, J. and Morgenstern, O., Theory of Games and Economic Behavior, Princeton University Press, 1944, ISBN-13: 978-0-691-13061-3.

24) P. Yu, Multiple Criteria Decision Making: Concepts, Techniques and Extensions, Plenum Press, 1985, ISBN (13): 978-1-468-48395-6.

25) Constantin Zopounidis and Michael Doumpos, Multiple Criteria Decision Making: Applications in Management and Engineering, Springer, 2017, ISBN (13): 978-3-319-39292-9.

Instructor bio

Prof. Raghu Nandan Sengupta

IIT Kanpur

Prof. Raghu Nandan Sengupta is at present a full Professor in the IME Department at IIT Kanpur, INDIA where he has been a faculty member since 2003. He research areas are in Theoretical Statics, Sequential Analysis, Decision Analysis, Quantitative Finance, Reliability and Robust Optimization with Applications etc. He has published in journals like EJOR, Communications in Statistics, Metrika, Journal of Applied Statistics, Quantitative Finance, Annals of Operations Research, Sankhya, Computational Statistics and Data Analysis, Foundations of Computing and Decision Sciences, Journal of Marketing Theory and Practice, etc. He also has two books to his credit namely: Decision Sciences: Theory and Practice (CRC Taylor & Francis) and Studies in Quantitative Decision Making (Springer). Raghu Nandan Sengupta has also been the Head of IME department, Vice Chairman JEE Advanced and Vice Chairman GATE/JAM (Organizing). He has also been awarded the IUSSTF, DAAD, ERASMUS, EU-NAMASTE Fellowships. His teaching interests are: Probability & Statistics, Management Decision Analysis, Project Management, Investment & Portfolio Analysis, Total Quality Management, econometrics, Stochastic Process, etc.

Course certificate

The course is free to enroll and learn from. But if you want a certificate, you have to register and write the proctored exam conducted by us in person at any of the designated exam centres.

The exam is optional for a fee of Rs 1000/- (Rupees one thousand only).

Date and Time of Exams: : April 19, 2026 Morning session 9am to 12 noon; Afternoon Session 2pm to 5pm.

Registration url: Announcements will be made when the registration form is open for registrations.

The online registration form has to be filled and the certification exam fee needs to be paid. More details will be made available when the exam registration form is published. If there are any changes, it will be mentioned then.

Please check the form for more details on the cities where the exams will be held, the conditions you agree to when you fill the form etc.

CRITERIA TO GET A CERTIFICATE

Average assignment score = 25% of average of best 8 assignments out of the total 12 assignments given in the course.
Exam score = 75% of the proctored certification exam score out of 100

Final score = Average assignment score + Exam score

Please note that assignments encompass all types (including quizzes, programming tasks, and essay submissions) available in the specific week.

YOU WILL BE ELIGIBLE FOR A CERTIFICATE ONLY IF AVERAGE ASSIGNMENT SCORE >=10/25 AND EXAM SCORE >= 30/75. If one of the 2 criteria is not met, you will not get the certificate even if the Final score >= 40/100.

Certificate will have your name, photograph and the score in the final exam with the breakup.It will have the logos of NPTEL and IIT Kanpur .It will be e-verifiable at nptel.ac.in/noc.

Only the e-certificate will be made available. Hard copies will not be dispatched.

Once again, thanks for your interest in our online courses and certification. Happy learning.

- NPTEL team