Dogus University IE402 Introduction to Multi-criteria Decision Analysis

Due to COVID-19 precautions this semester will continue online.

2019-2020 Spring Semester Course Instructions

  • Faculty: Engineering
  • Department: Industrial Engineering
  • ECTS: 6
  • Course Type: Elective


There is no main textbook adopted, however please refer to Recommended Texts.

Course Description

his course helps improve the quality of the choices in managerial and personal decisions involving multi-criteria and major uncertainties. It provides methods to help structure decision problems and analyze them quantitatively.


The purpose of this course is to introduce the most widely used multi-criteria decision making methodologies. The course will start with basic methods including models for decision-making under conditions of uncertainty or multiple criteria and techniques of risk analysis and risk assessment. This course aims to improve the understanding of quantitative decision making. Specifically, the course objectives are to: develop an understanding of how quantitative tools and analysis may lead to improved decision making and, improve the quantitative reasoning ability.

Learning Objectives

The students passing the course will be able to (The letters in parentheses addresses the relevant program outcomes)

  1. Learn the basic concepts of decision making, how to develop decision based models, (1b,8,10a)
  2. Learn specific methods for structuring and analyzing decisions.  (1b,8)
  3. Understand quantitative models, processes and tools for helping to structure and explore decisions characterized by multiple criteria, uncertainty, complexity and differences of opinion. (8,10a)
  4. Solve multi-criteria decision making models  (1b,8,10a)

Corresponding Program Outcomes

1b. Ability to apply theoretical and practical knowledge of these fields for modeling and solving complex engineering problems. (Medium contribution)

8. Recognition of the need for lifelong learning; ability to access knowledge, to pursue the developments in science and technology, and to remain up to date. (High contribution)

10a. Knowledge about professional applications such as project, risk, and change management. (Low contribution)


1 Homework (5%)

1 Term Project (15%)

1 Final Exam (80%)