School of Engineering and Technology, (SET)
 
AT72.07 : Multicriterion Decision Models  3(3-0)
 
Course objectives:
Traditional decision models are monocriterion and are handicapped in real-life applications. This course is designed to extend these important decision models from monocriterion to a more realistic multicriterion framework. General approaches and specific techniques which are practical are presented.
 
Learning Outcomes:
Multiple Criteria Decision Making. Theoritical Foundations and Concepts. Preference Information Generation. Multiobjective Decision Models. Multiattribute Decision Models. MCDM Extensions. Case Studies.
 
Pre-requisite(s):
Consent of Instructor
 
Course Outline:

I Multiple Criteria Decision Making
1. Multiple Aspirations of Organizations
2. Definitions - Criteria, Objectives, Attributes, Goals and Targets
3. Conflict of Criteria/Objectives
4. Decision Making Approaches

II Theoretical Foundations and Concepts
1. Necessary and Sufficient Conditions
2. Optimizing versus “Satisficing”
3. Efficiency/ Noninferiority/Pareto Optimality/Nondominance
4. Dimensionality

III Preference Information Generation
1. Priorities, Weights and Tradeoffs
2. Ordinal versus Cardinal and Implicit versus Explicit Preference
3. Ranking, Rating and Paired Comparison Methods
5. Value and Utility Theories
6. Game Theory

IV Multiobjective Decision Models
1. Global Criterion Method
2. Maximum Effectiveness Method
3. Goal Programming
4. Compromise Programming and Compromise Constraint Method
5. Interactive Models: Step Method and Game Theoretic Method
6. Parametric Method

V Multiattribute Decision Models
1. Analytic Hierarchy Process
2. Multiattribute Value/Utility Theory
3. ELECTRE and PROMETHEE Methods
4. Aspiration Level Interactive Method
5. Other Outranking Methods

VI MCDM Extensions
1. Nonlinear MCDM
2. Stochastic MCDM
3. Fuzzy MCDM
4. ANP Method
5. Group Decision Making

VII Case Studies

 

 
 
Learning Resources:

Textbook:
Lecture Notes.
 
Reference Books:
M.T. Tabucanon, Multiple Criteria Decision Making in Industry, Elsevier, Amsterdam, 1988.
Masatoshi Sakawa, Large Scale Interacive Fuzzy Multiobjective Programming: Decomposition Approach, Springer-Verlag, New York, 2000.
R.E. Steuer, Multi Criteria Optimization: Theory, Computation and Application, John Wiley, 1986.
R. Slowinski and J. Teghem (eds.), Stochastic versus Fuzzy Approaches to Multiobjective Mathematical Programming Problems under Uncertainty, Kluwer Academic Publishers, Dordrecht, 1990.
P.Vincke, M. Gassner and B. Roy, Multicriteria Decision Aid, John Wiley, 1989.
M. Zeleny, Multiple Criteria Decision Making, McGraw-Hill, 1982.
K. P. Miettinen, Nonlinear Multiobjective Optimization, Kluwer Academic Publishers, 1998.
Valerie Belton, Theodor J. Stewart, Multiple Criteria Decision Analysis, Kluwer Academic Publishers, 2002.
 
Journals and Magazines:
Operations Research
Management Science
European Journal of Operational Research
Decision Science
IEEE Transaction on Systems, Man and Cybernetics, Parts A and B.
Computers and Operations Research
 
 
 
Evaluation Scheme:
The Final Grade will be computed according to the following weight distribution: Midsemester Exam 30%; Final Exam 50%; Assignments/Project 20%.
All examinations will normally be closed book.
 
Instructor(s):
SECTION NAME