Operations Research I (IE222) Course Detail

Course Name	Course Code	Season	Lecture Hours	Application Hours	Lab Hours	Credit	ECTS
Operations Research I	IE222	Area Elective	3	2	0	4	7.5

Pre-requisite Course(s)
MATH275

Course Language	English
Course Type	Elective Courses
Course Level	Bachelor’s Degree (First Cycle)
Mode of Delivery	Face To Face
Learning and Teaching Strategies	Drill and Practice, Problem Solving.
Course Coordinator
Course Lecturer(s)	Asst. Prof. Dr. Barış YILDIZ Research Assistant İrem BULANIK
Course Assistants
Course Objectives	Students should have the ability to model and solve real-life problems using linear programming techniques and analyze results obtained with such models. Students should be able to use software to solve a variety of models.
Course Learning Outcomes	The students who succeeded in this course; Will acquire knowledge sufficient to use the deterministic O.R techniques, primarily the linear programming. Will be able to develop an appropriate model from a verbal description of a problem. Will be able to choose an approximate solution technique and solve engineering problems. Will be able to interpret relevant information from a model and/or a solution and interpret it. Will be able to develop and solve Linear Programming models using appropriate software packages.
Course Content	Historical development of operations research, modeling, graphical solution, Simplex and dual Simplex methods, duality and sensitivity analysis, transportation, assignment, and transshipment problem.

Weekly Subjects and Releated Preparation Studies

Week	Subjects	Preparation
1	Introduction to OR	[1] pg. 1-9
2	Modeling Approaches in Linear Programming	[1] pg. 49-126
3	Modeling Approaches in Linear Programming	[1] pg. 49-126
4	Modeling Approaches in Linear Programming	[1] pg. 49-126
5	The Graphical method	[1] pg. 50-99
6	The Simplex Algorithm	[1] pg. 126-189, [2] pg. 91-107
7	The Simplex Algorithm	[1] pg. 126-189, [2] pg.125-134
8	The Simplex Algorithm	[2] pg. 220-234
9	The Simplex Algorithm	[1] pg. 126-189, [2] pg. 154-165
10	Duality, Midterm Exam	[1] pg. 295-334
11	Duality	[1] pg. 295-334, [2] pg. 277-284
12	Sensitivity Analysis	[1] pg. 202-294
13	Sensitivity Analysis	[1] pg. 202-294
14	Transportation Problem	[1] pg. 360-392
15	Transportation Problem	[1] pg. 360-392
16	Final Exam

Sources

Course Book	1. Winston, W.L., Operations Research: Applications and Algorithms, 4th Edition, Brooks/Cole-Thomson Learning, 2004.
Other Sources	2. Bazaraa, M.S., Jarvis, J.J., and Sherali, H.D., Linear Programming and Network Flows, 4th Edition, John Wiley & Sons, 2010.
	3. Frederick S. Hillier and Gerald J. Lieberman, Introduction to Operations Research and Revised CD-ROM 8, McGraw-Hill Science, 2005.
	4. WU, N. and COPPINS, R., Linear Programming and Extensions, Cambridge University Press, 1981.
	5. Anderson D. R., Sweeney D. J., and Williams T. A., An Introduction to Management Science, 11th Edition, West, 2004.
	6. Taha, H. A., Operations Research: An Introduction, 8th Edition, Prentice Hall, 2006.

Evaluation System

Requirements	Number	Percentage of Grade
Attendance/Participation	-	-
Laboratory	-	-
Application	-	-
Field Work	-	-
Special Course Internship	-	-
Quizzes/Studio Critics	7	20
Homework Assignments	-	-
Presentation	-	-
Project	-	-
Report	-	-
Seminar	-	-
Midterms Exams/Midterms Jury	1	35
Final Exam/Final Jury	1	45
Toplam	9	100

Percentage of Semester Work	55
Percentage of Final Work	45
Total	100

Course Category

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

The Relation Between Course Learning Competencies and Program Qualifications

#	Program Qualifications / Competencies	Level of Contribution
#	Program Qualifications / Competencies	1	2	3	4	5
1	Acquires skills to use the advanced theoretical and applied knowledge obtained at the mathematics bachelors program to do further academic and scientific research in both mathematics-based graduate programs and public or private sectors.
2	Transplants and applies the theoretical and applicable knowledge gained in their field to the secondary education by using suitable tools and devices.
3	Acquires the skill of choosing, using and improving problem solving techniques which are needed for modeling and solving current problems in mathematics or related fields by using the obtained knowledge and skills.
4	Acquires analytical thinking and uses time effectively in the process of deduction.
5	Acquires basic software knowledge necessary to work in the computer science related fields and together with the skills to use information technologies effectively.
6	Obtains the ability to collect data, to analyze, interpret and use statistical methods necessary in decision making processes.
7	Acquires the level of knowledge to be able to work in the mathematics and related fields and keeps professional knowledge and skills up-to-date with awareness in the importance of lifelong learning.
8	Takes responsibility in mathematics related areas and has the ability to work affectively either individually or as a member of a team.
9	Has proficiency in English language and has the ability to communicate with colleagues and to follow the innovations in mathematics and related fields.
10	Has the ability to communicate ideas with peers supported by qualitative and quantitative data.
11	Has professional and ethical consciousness and responsibility which takes into account the universal and social dimensions in the process of data collection, interpretation, implementation and declaration of results in mathematics and its applications.

ECTS/Workload Table

Activities	Number	Duration (Hours)	Total Workload
Course Hours (Including Exam Week: 16 x Total Hours)	16	3	48
Laboratory
Application	16	2	32
Special Course Internship
Field Work
Study Hours Out of Class	16	4	64
Presentation/Seminar Prepration
Project
Report
Homework Assignments
Quizzes/Studio Critics	7	1	7
Prepration of Midterm Exams/Midterm Jury	1	14	14
Prepration of Final Exams/Final Jury	1	24	24
Total Workload			189