Decision Analysis (IE 405)

2020 Spring
Faculty of Engineering and Natural Sciences
Industrial Engineering(IE)
6.00 / 6.00 ECTS (for students admitted in the 2013-14 Academic Year or following years)
Hans Frenk,
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Formal lecture,Recitation
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Introduction to the theory and practice of decision processes under uncertainty; use of decision trees and influence diagrams in solving decision-making problems; assessing probabilities in modeling uncertainty; Bayesian statistical analysis; value of information; attitudes towards risk; and utility theory.


The course provides a broad practical overview of topics and techniques in the field of decision analysis. As an engineering course for undergraduate students, the course will address advanced technical subjects that can be found in management science and operations research domains. At the end of the term, the students will be able to formulate decision making problems that have multiple decisions in time, uncertain events, and conflicting objectives. We will also discuss certain behavioral issues related to decision making.


Describe the objectives, alternatives and uncertainties in a decision problem
Model and solve decision problems using decision trees.

Conduct sensitivity analysis to understand the important variables in the decision problem.
Explain the concepts of strategy, risk profiles and dominance.
Apply Bayes' formula, and calculate the values of perfect and imperfect information.
Assess discrete and continuous probability distributions using subjective methods, approximate methods, as well as theoretical models.
Apply single and multi-attribute utility models.
Implement the Analytical Hierarchy Process (AHP).
Describe the fundamental decision heuristics and related biases.
Discuss the fundamental concepts and trade-offs in decision analysis.


1. Understand the world, their country, their society, as well as themselves and have awareness of ethical problems, social rights, values and responsibility to the self and to others. 4

2. Understand different disciplines from natural and social sciences to mathematics and art, and develop interdisciplinary approaches in thinking and practice. 4

3. Think critically, follow innovations and developments in science and technology, demonstrate personal and organizational entrepreneurship and engage in life-long learning in various subjects. 3

4. Communicate effectively in Turkish and English by oral, written, graphical and technological means. 3

5. Take individual and team responsibility, function effectively and respectively as an individual and a member or a leader of a team; and have the skills to work effectively in multi-disciplinary teams. 3

1. Develop knowledge of theories, concepts, and research methods in humanities and social sciences. 3

2. Assess how global, national and regional developments affect society. 1

3. Know how to access and evaluate data from various sources of information. 3

1. Possess sufficient knowledge of mathematics, science and program-specific engineering topics; use theoretical and applied knowledge of these areas in complex engineering problems. 3

2. Identify, define, formulate and solve complex engineering problems; choose and apply suitable analysis and modeling methods for this purpose. 4

3. Develop, choose and use modern techniques and tools that are needed for analysis and solution of complex problems faced in engineering applications; possess knowledge of standards used in engineering applications; use information technologies effectively. 4

4. Ability to design a complex system, process, instrument or a product under realistic constraints and conditions, with the goal of fulfilling specified needs; apply modern design techniques for this purpose. 3

5. Design and conduct experiments, collect data, analyze and interpret the results to investigate complex engineering problems or program-specific research areas. 3

6. Knowledge of business practices such as project management, risk management and change management; awareness on innovation; knowledge of sustainable development. 4

7. Knowledge of impact of engineering solutions in a global, economic, environmental, health and societal context; knowledge of contemporary issues; awareness on legal outcomes of engineering solutions; understanding of professional and ethical responsibility. 4

1. Demonstrate an understanding of economics, and main functional areas of management. 3

2. Assess the impact of the economic, social, and political environment from a global, national and regional level. 4

1. Formulate and analyze problems in complex manufacturing and service systems by comprehending and applying the basic tools of industrial engineering such as modeling and optimization, stochastics, statistics. 5

2. Design and develop appropriate analytical solution strategies for problems in integrated production and service systems involving human capital, materials, information, equipment, and energy. 4

3. Implement solution strategies on a computer platform for decision-support purposes by employing effective computational and experimental tools. 4

1. Familiarity with concepts in statistics and optimization, knowledge in basic differential and integral calculus, linear algebra, differential equations, complex variables, multi-variable calculus, as well as physics and computer science, and ability to use this knowledge in modeling, design and analysis of complex dynamical systems containing hardware and software components. 2

2. Ability to work in design, implementation and integration of engineering applications, such as electronic, mechanical, electromechanical, control and computer systems that contain software and hardware components, including sensors, actuators and controllers. 2

1. Pursue open minded inquiry and appreciate the importance of research as an input into management practice. 3

2. Know how to access, interpret and analyze data and information and use them to make informed decisions. 5

3. Work effectively in environments characterized by people of diverse educational, social and cultural backgrounds. 2

4. Identify, select, and justify strategies and courses of action at the divisional, business, and corporate levels of analysis and to develop effective plans for the implementation of selected strategies. 4

1. Applying fundamental and advanced knowledge of natural sciences as well as engineering principles to develop and design new materials and establish the relation between internal structure and physical properties using experimental, computational and theoretical tools. 1

2. Merging the existing knowledge on physical properties, design limits and fabrication methods in materials selection for a particular application or to resolve material performance related problems. 1

3. Predicting and understanding the behavior of a material under use in a specific environment knowing the internal structure or vice versa. 1

1. Design, implement, test, and evaluate a computer system, component, or algorithm to meet desired needs and to solve a computational problem. 2

2. Demonstrate knowledge of discrete mathematics and data structures. 1

3. Demonstrate knowledge of probability and statistics, including applications appropriate to computer science and engineering. 3


  Percentage (%)
Final 40
Midterm 30
Exam 20
Participation 10



Making Hard Decisions with Decision Tools, 2nd Edition by Robert T. Clemen, Duxbury, 2003