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

General course introduction information

Course Code:

IE322

Course Name:

Operations Research II

Course Semester:

Spring

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:	I. Guiding students in formulating problems and finding appropriate solutions, algorithms or heuristics to solve them. II. Teaching students how to tackle non-linear, integer and dynamic programming problems.
Course Content:	This course aims to guide students in formulating problems and finding appropriate solutions, algorithms or heuristics to solve them and teach students how to tackle non-linear, integer and dynamic programming problems.

Learning Outcomes

The students who have succeeded in this course;

Learning Outcomes

1 - Knowledge
Theoretical - Conceptual
2 - Skills
Cognitive - Practical
1) Formulate and Solve Integer Programming Problems
2) II. Formulate and Solve Non-Linear Programming Problems
3) Gain competence in Goal Programming and Project Planning
4) Formulate and Solve Dynamic Programming Problems
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)	-Modeling Techniques -LP relief forms and graphics solutions	Lecture notes
2)	-Integer Programming -Cutting plane algorithm -Pure IP solution with the branch and bound technique	Lecture notes
3)	-Mixed IP solution with branch and bound technique -Branch and bound technique to solving the Knapsack Problem	Lecture notes
4)	-Modelling and solving IP problems (general review)	Lecture notes
5)	-Non-Linear programming -Modeling Techniques -Convex and concave functions	Lecture notes
6)	-Univariate NLP solutions -Multivariable unconstrained NLP solutions -Lagrange multiplier method -Kuhn Tucker conditions	Lecture notes
7)	Midterm	Exam questions
8)	-Goal programming -Weighted goal programming -Primary objective programming -Target programming Simplex method	Lecture notes
9)	-Quadratic Programming -Wolfe method -Removable programming	Lecture notes
10)	-Dynamic programming concept -DPA solution with the shortest path problem	Lecture notes
11)	-Solving the Knapsack Problem with DP -Inventory solution with the DP models	Lecture notes
12)	-Stochastic dynamic programming -Solutions to stochastic inventory model with DP	Lecture notes
13)	-Project Management: Critical Path Method -Project Management: Program Evaluation and Review Technique	Lecture notes
14)	General review	Lecture notes

Sources

Course Notes / Textbooks:

Winston, W., (2004) "Operations Research: Applications and Algorithms" 4th Ed., Wadsworth Inc., USA

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	2	3	4
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