Decision Analysis

Course Code:

ISE 432

Course Period:

Spring

Course Type:

Core

Credits:

3

Theoric:

2

Practice:

1

Laboratory Hour:

1

ECTS:

6

Prerequisite Courses:

Operations Research II

Statistical Applications for Industrial Engineers

Course Language:

English

Course Objectives:

introducing decision analysis, a process that provides a structured method with analytical tools designed to improve one’s decision-making skills.

Course Content:

This course provides an overview of decision analysis for advanced undergraduate students. The objective of decision analysis is to help a decision maker think hard about the specific problem at hand, including the overall structure of the problem as well as his or her preferences and beliefs. Decision analysis provides both an Content overall paradigm and a set of tools with which a decision maker can construct and analyze a model of a decision situation. Above all else, students need to understand that the purpose of studying decision-analysis techniques is to be able to represent real-world problems using models that can be analyzed to gain insight and understanding.

Course Methodology:

1: Lecture by instructor, 2: Lecture by instructor with class discussion, 3: Problem solving by instructor, 4: Use of simulations, 5: Problem solving assignment, 6: Reading assignment, 7: Laboratory work, 8: Term research paper, 9: Presentation by guest s

Course Evaluation Methods:

A: Written exam, B: Multiple-choice exam C: Take-home quiz, D: Experiment report, E: Homework, F: Project, G: Presentation by student

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Course Learning Outcomes

Course Learning Outcomes	Detailed Program Outcomes	Teaching Methods	Assessment Methods
Ability to think hard about a decision context and elicit the decision nodes, the uncertainty nodes and their sequence. In addition, drawing the influence diagram and solving the decision tree.	1a, 1b	1, 2, 3	A, C, F
Ability to figure out the possible strategies in a decision context and drawing the risk profiles of different strategies to understand the possibility of dominance among available strategies.	2a, 2b, 3a, 3b	1, 2, 3	A, C, F
Ability to run sensitivity analysis (one-way/two way) on various uncertainty nodes and determining the strategy regions.	2a, 2b	1, 2, 3	A, C, F
Capability of incorporating information in the decision context and (perfect or imperfect) and calculating the value of information in the mentioned decision context.	2a, 2b, 3a, 3b	1, 2, 3	A, C, F
Capability of Modeling risk preferences for different individuals by assigning different utility functions (DARA, CARA) and distinguishing the difference between risk attitudes.	10a	1, 2, 3	A, C, F
Finalizing a group project by modeling a real-life decision context with plausible uncertainties and decision sequences and distinguishing the consequences of assigning different utility functions in terms of their preferences besides determining the possible dominant strtategies, effect of information and etc.	3a,3b,4a, 4b, 6a, 6c, 7c, 10a	1, 2, 3, 8, 12	A, C, F

Course Flow

COURSE CONTENT
Week		Topics		Study Materials
1		Chapter 1: Modeling Decisions		Textbook and Lecture Notes
2		Chapter 2: Elements of Decision Problems		Textbook and Lecture Notes
3		Chapter 3: Structuring Decisions		Textbook and Lecture Notes
4		Chapter 3: Making Choices		Textbook and Lecture Notes
5		Chapter 4: Risk Profiles and Dominance (Stochastic or Deterministic)		Textbook and Lecture Notes
6		Chapter 5: Sensitivity Analysis		Textbook and Lecture Notes
7		Midterm and Review Session		Textbook and Lecture Notes
8	Chapter 8: Subjective Probability		Textbook and Lecture Notes
9	Chapter 9: Theoretical Probability Models		Textbook and Lecture Notes
10	Chapter 10: Using Data		Textbook and Lecture Notes
11	Chapter 12: Value of Information		Textbook and Lecture Notes
12	Chapter 14: Utility Functions & Risk Attitudes		Textbook and Lecture Notes
13	Chapter 14: DARA, CARA, IARA models		Textbook and Lecture Notes
14	Review and Problem Session		Textbook and Lecture Notes

Recommended Sources

RECOMMENDED SOURCES

Textbook Robert T. Clemen_ Terence Reilly - Making Hard Decisions with Decision tools-Cengage Learning (2013)

Material Sharing

MATERIAL SHARING

Documents Lecture Notes

Exams 1 Midterm, Final,2 Quiz

Assessment

ASSESSMENT
IN-TERM STUDIES	NUMBER		PERCENTAGE
Mid-term Exam	1		30
Quiz (the lowest quiz grade will not be considered)	2	10
Project	1	30
Total			70
CONTRIBUTION OF FINAL EXAMINATION TO OVERALL GRADE			30
CONTRIBUTION OF IN-TERM STUDIES TO OVERALL GRADE			70
Total			100

Course’s Contribution to Program

COURSE'S CONTRIBUTION TO PROGRAM OUTCOMES
No	Program Learning Outcomes	check X
1a	Adequate knowledge in mathematics, science and engineering subjects pertaining to the relevant discipline,	X
1b	Ability to use theoretical and applied knowledge in these areas in complex engineering problems.	X
2a	Ability to identify, formulate, and solve complex engineering problems,	X
2b	Ability to select and apply proper analysis and modeling methods for this purpose.	X
3a	Ability to design a complex system, process, device or product under realistic constraints and conditions, in such a way as to meet the desired result,	X
3b	Ability to apply modern design methods for this purpose.	X
4a	Ability to devise, select and use modern techniques and tools needed for analyzing and solving complex problems encountered in engineering practice.	X
4b	Ability to employ information technologies effectively.	X
5a	Ability to design experiments for investigating complex engineering problems or discipline specific research questions,
5b	Ability to conduct experiments, gather data, analyze and interpret results for investigating complex engineering problems or discipline specific research questions.
6a	Ability to work efficiently in intra-disciplinary teams,	X
6b	Ability to work efficiently in multi-disciplinary teams,
6c	Ability to work individually.	X
7a	Ability to communicate effectively both orally and in writing,
7b	Knowledge of a minimum of one foreign language,
7c	Ability to write effective reports and comprehend written reports, prepare design and production reports,	X
7d	Ability to make effective presentations,
7e	Ability to give and receive clear and intelligible instructions.
8a	Recognition of the need for lifelong learning, ability to access information, ability to follow developments in science and technology,
8b	Ability to continue to educate him/herself.
9a	Consciousness to behave according to ethical principles and professional and ethical responsibility.
9b	Knowledge on standards used in engineering practice.
10a	Knowledge about business life practices such as project management, risk management, change management.	X
10b	Awareness in entrepreneurship and innovation.
10c	Knowledge about sustainable development.
11a	Knowledge about the global and social effects of engineering practices on health, environment, and safety,
11b	Knowledge about contemporary issues of the century reflected into the field of engineering.
11c	Awareness of the legal consequences of engineering solutions.

ECTS

ECTS ALLOCATED BASED ON STUDENT WORKLOAD BY THE COURSE DESCRIPTION
Activities	Quantity	Duration (Hour)	Total Workload (Hour)
Course Duration	14	4	56
Hours for off-the-classroom study (Pre-study, practice)	14	2	28
Project	1	14	14
Quiz	2	2	4
Midterms	1	13	13
Final	1	14	14
Total Work Load			129
Total Work Load / 25 (h)			5.16
ECTS Credit of the Course			5

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