Industrial Engineering

Decision Analysis(IND401)

Course Code Course Name Semester Theory Practice Lab Credit ECTS
IND401 Decision Analysis 7 3 0 0 3 4
Prerequisites IND371-IND211
Admission Requirements IND371-IND211
Language of Instruction English
Course Type Elective
Course Level Bachelor Degree
Course Instructor(s) Esra ALBAYRAK ealbayrak@gsu.edu.tr (Email)
Assistant
Objective This course helps improve the quality of the choices in managerial and personal decisions involving major uncertainties. It provides methods to help structure decision problems and analyze them quantitatively. Such methods include models for decision-making under conditions of uncertainty or multiple criteria, techniques of risk analysis and risk assessment.
Content Introduction to Decision Analysis, What is Decision Analysis? Basic concepts., Structuring Decision Problems, (alternatives, consequences, objectives, and uncertainties). Votation, Social Choice Theory and Social Choice Functions, Decision making under uncertainty (Models and Choices) Decision criteria (Maximin, Maximax, Minimax Regret, The Expected Value Criterion). Decision making under risk. What is Risk Analysis? Basic concepts. Decision trees and influence diagrams. Risk Attitudes, Risk Management and Risk Measurement, Utility Theory, Utility Assessment. the preference assessment procedures. Determination of the Decision-Maker’s Utility, Modeling Risk and Uncertainty, Modeling risk attitude Certainty valants, Influence Diagrams, Decision Trees and Decision Tables, Bayes’ Rule. Probability modeling and expert judgment. Expert Judgment and/or Group Participation. Decision Making Under Multiple Criteria (Analytic Hierarchy Process Topsis, Electre) echniques for weighting criteria. Sensitivity
robustness analysis. Game Theory
Course Learning Outcomes 1. Students will learn specific methods for structuring and analyzing decisions.
2. This course provides an introduction to models, processes and tools for helping to structure and explore decisions characterized by multiple criteria, uncertainty, complexity and differences of opinion.
Teaching and Learning Methods
References R. T. Clemen, Making Hard Decisions: An Introduction to Decision Analysis, 2nd Edition, Duxbury Press, Belmont, CA, 1996

Operations Research: An Introduction (8th Edition) Hamdi A. Taha

Operations Research: Applications and Algorithms Wayne L. Winston

Frederick S. Hillier, Gerald J. Lieberman, Introduction to Operations Research, Ninth Edition, 2010 Mc GrawHill.
Print the course contents
Theory Topics
Week Weekly Contents
1 Introduction to Decision Analysis, What is Decision Analysis? Basic concepts
2 Structuring Decision Problems, (alternatives, consequences, objectives, and uncertainties).
3 Votation, Social Choice Theory and Social Choice Functions
4 Decision making under uncertainty (Models and Choices) Decision criteria (Maximin, Maximax, Minimax Regret, The Expected Value Criterion)
5 Decision making under risk. What is Risk Analysis? Basic concepts. Decision trees and influence diagrams
6 Risk Attitudes, Risk Management and Risk Measurement
7 Utility Theory, Utility Assessment. the preference assessment procedures
8 Determination of the Decision-Maker’s Utility, Modeling Risk and Uncertainty, Modeling risk attitude Certainty Equivalants
9 Influence Diagrams, Decision Trees and Decision Tables
10 Bayes’ Rule. Probability modeling and expert judgment.
11 Bayes’ Rule. Probability modeling and expert judgment.
12 Decision Making Under Multiple Criteria (Analytic Hierarchy Process Topsis, Electre)
13 Techniques for weighting criteria. Sensitivity and robustness analysis
14 Game Theory
Practice Topics
Week Weekly Contents
Contribution to Overall Grade
  Number Contribution
Contribution of in-term studies to overall grade 2 60
Contribution of final exam to overall grade 1 40
Toplam 3 100
In-Term Studies
  Number Contribution
Assignments 0 0
Presentation 0 0
Midterm Examinations (including preparation) 2 60
Project 0 0
Laboratory 0 0
Other Applications 0 0
Quiz 0 0
Term Paper/ Project 0 0
Portfolio Study 0 0
Reports 0 0
Learning Diary 0 0
Thesis/ Project 0 0
Seminar 0 0
Other 0 0
Toplam 2 60
No Program Learning Outcomes Contribution
1 2 3 4 5
1 Knowledge and understanding of a wide range of basic sciences (math, physics, ...) and the main concepts of engineering X
2 Ability to combine the knowledge and skills to solve engineering problems and provide reliable solutions X
3 Ability to select and apply methods of analysis and modeling to ask, reformulate and solve the complex problems of industrial engineering X
4 Ability to conceptualize complex systems, processes or products under practical constraints to improve their performance, ability to use innovative methods of design X
5 Ability to design, select and apply methods and tools needed to solve problems related to the practice of industrial engineering, ability to use computer technology X
6 Ability to design experiments, collect and interpret data and analyze results X
7 Ability to work independently, ability to participate in working groups and have a multidisciplinary team spirit
8 Ability to communicate effectively, ability to speak at least two foreign languages X
9 Awareness of the need for continuous improvement of lifelong learning, ability to keep abreast of scientific and technological developments to use the tools of information management X
10 Awareness of professional and ethical responsibility
11 Knowledge of the concepts of professional life as "project management", "risk management" and "management of change" X
12 Knowledge on entrepreneurship, innovation and sustainability
13 Understanding of the effects of Industrial Engineering applications on global and social health, environment and safety.
14 Knowledge of the problems of contemporary society X
15 Knowledge of the legal implications of the practice of industrial engineering
Activities Number Period Total Workload
Class Hours 14 3 42
Working Hours out of Class 12 2 24
Assignments 0 0 0
Presentation 0 0 0
Midterm Examinations (including preparation) 2 9 18
Project 0 0 0
Laboratory 0 0 0
Other Applications 0 0 0
Final Examinations (including preparation) 1 16 16
Quiz 0 0 0
Term Paper/ Project 0 0 0
Portfolio Study 0 0 0
Reports 0 0 0
Learning Diary 0 0 0
Thesis/ Project 0 0 0
Seminar 0 0 0
Other 0 0 0
Total Workload 100
Total Workload / 25 4,00
Credits ECTS 4
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