Decision Analysis(IND401)
| Course Code | Course Name | Semester | Theory | Practice | Lab | Credit | ECTS |
|---|---|---|---|---|---|---|---|
| IND401 | Decision Analysis | 7 | 3 | 0 | 0 | 3 | 4 |
| Prerequisites | IND371 VE IND211 |
| Admission Requirements | IND371 VE IND211 |
| Language of Instruction | English |
| Course Type | Elective |
| Course Level | Bachelor Degree |
| Course Instructor(s) | Esra ALBAYRAK ealbayrak@gsu.edu.tr (Email) Elif DOĞU edogu@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. |
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 | |||||
| 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 |
| Midterm Examinations (including preparation) | 2 | 9 | 18 |
| Final Examinations (including preparation) | 1 | 16 | 16 |
| Total Workload | 100 | ||
| Total Workload / 25 | 4.00 | ||
| Credits ECTS | 4 | ||