FACULTY OF ENGINEERING

Department of Industrial Engineering

IE 251 | Course Introduction and Application Information

Course Name
Optimization I
Code
Semester
Theory
(hour/week)
Application/Lab
(hour/week)
Local Credits
ECTS
IE 251
Fall
2
2
3
6

Prerequisites
  MATH 250 To succeed (To get a grade of at least DD)
Course Language
English
Course Type
Required
Course Level
First Cycle
Mode of Delivery -
Teaching Methods and Techniques of the Course Group Work
Problem Solving
Case Study
Application: Experiment / Laboratory / Workshop
Course Coordinator
Course Lecturer(s)
Assistant(s)
Course Objectives This course is the first part of a two term sequence, aims to give students a good foundation in the theory and applications of linear programming problems as well as an appreciation of its potential applications extensively in such diverse areas as manufacturing, financial planning, health care, the military, public services etc.
Learning Outcomes The students who succeeded in this course;
  • Will be able to construct mathematical model of the problem
  • Will be able to use the simplex method for solving linear programming
  • Will be able to attempt to find an optimal or best solution for the problem under consideration
  • Will be able to perform a sensitivity analysis
  • Will be able to provide positive and understandable conclusions to decision maker
  • Will be able to implement Excel and OPL (the general algebraic modeling system) softwares to solve mathematical models
Course Description The main subjects of the course are the construction of linear programming models, the geometrical interpretation of solutions to the linear optimization problems and their algebraic groundwork, the simplex method, duality theory, sensitivity analysis and the dual simplex method.

 



Course Category

Core Courses
Major Area Courses
X
Supportive Courses
Media and Management Skills Courses
Transferable Skill Courses

 

WEEKLY SUBJECTS AND RELATED PREPARATION STUDIES

Week Subjects Related Preparation
1 Introduction Chapters 1 and 2: Introduction to Operations Research, Frederick S. Hillier, Gerald J. Lieberman
2 Introduction to Linear Programming Chapter 3: Introduction to Operations Research, Frederick S. Hillier, Gerald J. Lieberman
3 Introduction to Linear Programming Chapter 3: Introduction to Operations Research, Frederick S. Hillier, Gerald J. Lieberman
4 Introduction to Linear Programming Chapter 3: Introduction to Operations Research, Frederick S. Hillier, Gerald J. Lieberman
5 The Simplex Algorithm Chapters 4 and 5: Introduction to Operations Research, Frederick S. Hillier, Gerald J. Lieberman
6 The Simplex Algorithm Chapters 4 and 5: Introduction to Operations Research, Frederick S. Hillier, Gerald J. Lieberman
7 The Simplex Algorithm Chapters 4 and 5: Introduction to Operations Research, Frederick S. Hillier, Gerald J. Lieberman
8 Midterm Exam
9 The Simplex Algorithm Chapters 4 and 5: Introduction to Operations Research, Frederick S. Hillier, Gerald J. Lieberman
10 Sensitivity Analysis and Duality Chapter 6: Introduction to Operations Research, Frederick S. Hillier, Gerald J. Lieberman
11 Sensitivity Analysis and Duality Chapter 6: Introduction to Operations Research, Frederick S. Hillier, Gerald J. Lieberman
12 Sensitivity Analysis and Duality Chapter 7: Introduction to Operations Research, Frederick S. Hillier, Gerald J. Lieberman
13 Sensitivity Analysis and Duality Chapter 8: Introduction to Operations Research, Frederick S. Hillier, Gerald J. Lieberman
14 General Review, Discussion and Evaluation
15 Review of the Semester  
16 Review of the Semester  

 

Course Notes/Textbooks Introduction to Operations Research, Frederick S. Hillier, Gerald J. Lieberman, Tenth Edition, 2010 Mc GrawHill, ISBN: 9780071267670.
Suggested Readings/Materials Operations Research: Applications and Algorithms, Wayne L. Winston, 4th Ed., Duxbury Press, ISBN 0534209718. Operations Research. An Introduction, Hamdy A. Taha, Sixth Edition, 1997, PrenticeHall, ISBN 0132811723.

 

EVALUATION SYSTEM

Semester Activities Number Weigthing
Participation
Laboratory / Application
1
10
Field Work
Quizzes / Studio Critiques
1
20
Portfolio
Homework / Assignments
1
10
Presentation / Jury
Project
-
Seminar / Workshop
Oral Exams
Midterm
1
25
Final Exam
1
35
Total

Weighting of Semester Activities on the Final Grade
3
65
Weighting of End-of-Semester Activities on the Final Grade
1
35
Total

ECTS / WORKLOAD TABLE

Semester Activities Number Duration (Hours) Workload
Theoretical Course Hours
(Including exam week: 16 x total hours)
16
2
32
Laboratory / Application Hours
(Including exam week: '.16.' x total hours)
16
2
32
Study Hours Out of Class
14
4
56
Field Work
0
Quizzes / Studio Critiques
1
15
15
Portfolio
0
Homework / Assignments
1
15
15
Presentation / Jury
0
Project
-
0
Seminar / Workshop
0
Oral Exam
0
Midterms
1
14
14
Final Exam
1
16
16
    Total
180

 

COURSE LEARNING OUTCOMES AND PROGRAM QUALIFICATIONS RELATIONSHIP

#
Program Competencies/Outcomes
* Contribution Level
1
2
3
4
5
1

To have adequate knowledge in Mathematics, Science and Industrial Engineering; to be able to use theoretical and applied information in these areas to model and solve Industrial Engineering problems.

X
2

To be able to identify, formulate and solve complex Industrial Engineering problems by using state-of-the-art methods, techniques and equipment; to be able to select and apply proper analysis and modeling methods for this purpose.

X
3

To be able to analyze a complex system, process, device or product, and to design with realistic limitations to meet the requirements using modern design techniques.

X
4

To be able to choose and use the required modern techniques and tools for Industrial Engineering applications; to be able to use information technologies efficiently.

X
5

To be able to design and do simulation and/or experiment, collect and analyze data and interpret the results for investigating Industrial Engineering problems and Industrial Engineering related research areas.

6

To be able to work efficiently in Industrial Engineering disciplinary and multidisciplinary teams; to be able to work individually.

7

To be able to communicate effectively in Turkish, both orally and in writing; to be able to author and comprehend written reports, to be able to prepare design and implementation reports, to present effectively; to be able to give and receive clear and comprehensible instructions

8

To have knowledge about contemporary issues and the global and societal effects of Industrial Engineering practices on health, environment, and safety; to be aware of the legal consequences of Industrial Engineering solutions.

9

To be aware of professional and ethical responsibility; to have knowledge of the standards used in Industrial Engineering practice.

10

To have knowledge about business life practices such as project management, risk management, and change management; to be aware of entrepreneurship and innovation; to have knowledge about sustainable development.

11

To be able to collect data in the area of Industrial Engineering; to be able to communicate with colleagues in a foreign language.

12

To be able to speak a second foreign at a medium level of fluency efficiently.

13

To recognize the need for lifelong learning; to be able to access information, to be able to stay current with developments in science and technology; to be able to relate the knowledge accumulated throughout the human history to Industrial Engineering.

X

*1 Lowest, 2 Low, 3 Average, 4 High, 5 Highest

 


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