Course Summary

This course begins with a comparative review of conventional and advanced multiple attribute decision making (MADM) models in engineering practice. Next, a new application of particular MADM models in reliable material selection of sensitive structural components as well as a multi-criteria Taguchi optimization method is discussed. Other specific topics include dealing with uncertainties in material properties, incommensurability in decision-makers opinions for the same design, objective ways of weighting performance indices, rank stability analysis, compensations and non-compensations.

This IAP course is open to all graduate students and researchers for registration or audition. Those who register, however, will be recognized for two credits after passing a take-home exam and conducting a project at the end of the course. The course readings are selected to strengthen students' awareness of both the theory and practice of the related areas.


Take-home Exam 60%
Project 40%

Course Calendar


Course Introduction, Definitions, Multiple Attribute Decision Making (MADM) vs. Multiple Objective Decision Making/Optimization, Different Mathematical and Hierarchical Classification of MADM and MODM Models, Beam Multiobjective Optimization Examples (Pareto frontier)

Examples of Weighting Techniques: Direct Assignment/Weighting from Ranks, Entropy, Eigenvector/Ratio Weighting


Examples of Compensatory MADM Models: Weighted Sum Model, Weighted Product Model, Additive Utility Theory, TOPSIS

Examples of Methods for Qualitative Data: Median Ranking Method, Analytical Hierarchy Process (AHP), Revised AHP, Analytical Network Processes (ANP)


Examples of Non-Compensatory MADM Models: Dominance, Satisfying Methods (Subjunctive and Disjunctive), Lexicographic, Elimination by Aspects, Modified Maximin-Maximax

Outranking Approach (ELECTRE I), ELECTRE III (Pseudo-Fuzzy), PROMETHEE I & II


Multiple Criteria Material Selection Procedure for Multi-Materials (e.g., Composites)

Recent Compensatory Approaches in Material Selection: A Novel Non-Linear Normalization and a Modified Digital Logic Method; Using Graph Theory and Matrix Approach

A Revised Simos Procedure as Weighting Tool for Designers: Group Decision Making

A Nonaggregative MADM Approach in Material Selection (for Ranking and Classification); Different Forms of Uncertainties; Performance Index Derivation; Rank Stability Analysis

An Application in Taguchi Design of Experiments Method: Case Study in an FEM-Based Multi-Criteria Design Optimization of a Forming Process