Madm with applications in material selection and optimal design

Lectures: 4 sessions / week, 3 hours / session

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.

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

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