Industrial Engineering (English)
Bachelor	TR-NQF-HE: Level 6	QF-EHEA: First Cycle	EQF-LLL: Level 6

General course introduction information

Course Code:

IE321

Course Name:

Operations Research I

Course Semester:

Fall

Course Credits:

Theoretical	Practical	Credit	ECTS
3	0	3	7

Language of instruction:

Course Requisites:

Does the Course Require Work Experience?:

Type of course:

Compulsory

Course Level:

Bachelor

TR-NQF-HE:6. Master`s Degree

QF-EHEA:First Cycle

EQF-LLL:6. Master`s Degree

Mode of Delivery:

Face to face

Course Coordinator :

Ar.Gör. AHMET SELÇUK YALÇIN

Course Lecturer(s):

Dr.Öğr.Üyesi GÜNSELİ GÖRÜR

Course Assistants:

Course Objective and Content

Course Objectives:	The objective of this course is to learn using different mathematical modeling techniques with OR, to learn using different methods that are used for numerical decision making, and to learn finding optimal solutions to problems.
Course Content:	I. To learn using different mathematical modeling techniques with Operations Research II. To learn using different methods that are used for numerical decision making III. To learn finding optimal solutions to problems

Learning Outcomes

The students who have succeeded in this course;

Learning Outcomes

1 - Knowledge
Theoretical - Conceptual
1) Use different mathematical modeling techniques
2) Comprehend the solution of a linear programming problem
2 - Skills
Cognitive - Practical
1) Solve a linear programming problem
2) Understand the sensitivity of a solution to the changes of parameters of a linear model
3) Use some computer software to model, solve and analyze a linear model
4) Identify whether a solution is optimal or not
5) Solve and analyze transportation and assignment problems with some dedicated methods
3 - Competences
Communication and Social Competence
Learning Competence
Field Specific Competence
Competence to Work Independently and Take Responsibility

Lesson Plan

Week	Subject	Related Preparation
1)	• Definition of operation research (OR), • Emergence of OR, • Steps of OR. • Basic concepts.	Lecture Notes
2)	• Introduction to Linear Programming	Ders notları
3)	• Linear Programming • Characteristics, • Assumptions and Modeling of LP, • Optimization concept	Lecture Notes
4)	Development of linear programming models.	Lecture notes
5)	Development of linear programming models and solving linear programming models with the graphical method.	Lecture Notes
6)	Solving linear programming model with the Simplex Algorithm	Lecture notes
7)	Evaluating students via midterm exam.	Preparing the exam
8)	• Artificial starting solution in the simplex algorithm, • M method	Lecture notes
9)	• Artificial starting solution in the simplex algorithm, • Two-Phase method	Lecture Notes
10)	Renewal of the past two weeks	Lecture Notes
11)	Duality, Dual simplex method	Lecture notes
12)	Sensitivity Analysis and Duality	Lecture notes
13)	Transportation Models	Lecture notes
14)	Transportation Simplex and the Hungarian Method	Lecture notes

Sources

Course Notes / Textbooks:

Winston W.L. (2004) “Operations Research: Applications and Algorithms”, Brooks/Cole – Thomson Learning

References:

I. Taha H.A. (2003) "Operations Research: An Introduction", Pearson Education Inc.
II. Taha H.A. (2000) "Yoneylem Arastirmasi", Literatur Yayincilik (cev. Alp Baray ve Sakir Esnaf)
III. Winston W.L., Albright S.C. (2001) "Practical Management Science", Duxbury Press, Wadsworth Inc.
IV. Render B., Stair R.M. Jr., Hanna M.E. (2003) "Quantitative Analysis for Management", Pearson Education Inc.
V. Taylor B.W. III (2002) "Introduction to Management Science", Pearson Education Inc
VI. Rardin R.L. (1998) "Optimization in Operations Research", Prentice Hall Inc.
VII. Walker R.C. (1999) "Introduction to Mathematical Programming", Prentice Hall Inc.

Course-Program Learning Outcome Relationship

Learning Outcomes	1	3	2	4	5	6	7
Program Outcomes
1) Adequate knowledge in mathematics, science and engineering subjects pertaining to the relevant discipline; ability to use theoretical and applied information in these areas to model and solve engineering problems.
2) Ability to identify, formulate, and solve complex engineering problems; ability to select and apply proper analysis and modelling methods for this purpose.
3) Ability to design a complex system, process, device or product under realistic constraints and conditions, in such a way so as to meet the desired result; ability to apply modern design methods for this purpose. (Realistic constraints and conditions may include factors such as economic and environmental issues, sustainability, manufacturability, ethics, health, safety issues, and social and political issues according to the nature of the design.)
4) Ability to devise, select, and use modern techniques and tools needed for engineering practice; ability to employ information technologies effectively.
5) Ability to design and conduct experiments, gather data, analyse and interpret results for investigating engineering problems.
6) Ability to work efficiently in intra-disciplinary and multi-disciplinary teams; ability to work individually.
7) Ability to communicate effectively i Turkish, both orally and in writing; knowledge of a minimum of one foreign language.
8) Recognition of the need for lifelong learning; ability to access information, to follow developments in science and technology, and to continue to educate him/herself.
9) Awareness of professional and ethical responsibility.
10) Information about business life practices such as project management, risk management, and change management; awareness of entrepreneurship, innovation, and sustainable development.
11) Knowledge about contemporary issues and the global and societal effects of engineering practices on health, environment, and safety; awareness of the legal consequences of engineering solutions.

Course - Learning Outcome Relationship

No Effect	1 Lowest	2 Low	3 Average	4 High	5 Highest

	Program Outcomes	Level of Contribution
1)	Adequate knowledge in mathematics, science and engineering subjects pertaining to the relevant discipline; ability to use theoretical and applied information in these areas to model and solve engineering problems.	5
2)	Ability to identify, formulate, and solve complex engineering problems; ability to select and apply proper analysis and modelling methods for this purpose.	4
3)	Ability to design a complex system, process, device or product under realistic constraints and conditions, in such a way so as to meet the desired result; ability to apply modern design methods for this purpose. (Realistic constraints and conditions may include factors such as economic and environmental issues, sustainability, manufacturability, ethics, health, safety issues, and social and political issues according to the nature of the design.)	5
4)	Ability to devise, select, and use modern techniques and tools needed for engineering practice; ability to employ information technologies effectively.	4
5)	Ability to design and conduct experiments, gather data, analyse and interpret results for investigating engineering problems.	1
6)	Ability to work efficiently in intra-disciplinary and multi-disciplinary teams; ability to work individually.
7)	Ability to communicate effectively i Turkish, both orally and in writing; knowledge of a minimum of one foreign language.
8)	Recognition of the need for lifelong learning; ability to access information, to follow developments in science and technology, and to continue to educate him/herself.	5
9)	Awareness of professional and ethical responsibility.	5
10)	Information about business life practices such as project management, risk management, and change management; awareness of entrepreneurship, innovation, and sustainable development.
11)	Knowledge about contemporary issues and the global and societal effects of engineering practices on health, environment, and safety; awareness of the legal consequences of engineering solutions.

Learning Activity and Teaching Methods

Lesson
Problem Solving

Assessment & Grading Methods and Criteria

Written Exam (Open-ended questions, multiple choice, true-false, matching, fill in the blanks, sequencing)

Assessment & Grading

Semester Requirements	Number of Activities	Level of Contribution
Midterms	1	% 50
Final	1	% 50
total		% 100
PERCENTAGE OF SEMESTER WORK		% 50
PERCENTAGE OF FINAL WORK		% 50
total		% 100

Workload and ECTS Credit Grading

Activities	Number of Activities	Duration (Hours)	Workload
Course Hours	14	3	42
Application	14	3	42
Study Hours Out of Class	14	8	112
Midterms	1	2	2
Final	1	2	2
Total Workload			200