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. Uğur BAÇ Research Assistant İrem BULANIK ÖZDEMİR Research Assistant Şevval KILIÇOĞLU
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; Students will acquire knowledge sufficient to use the deterministic O.R techniques, primarily the linear programming. Students will be able to develop an appropriate model from a verbal description of a problem. Students will be able to choose an approximate solution technique and solve engineering problems. Students will be able to interpret relevant information from a model and/or a solution and interpret it. Students 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	A review of basic linear algebra	[1] pg. 10-48
3	Introduction to Linear Programming	[1] pg. 49-126
4	Introduction to Linear Programming The Graphical method	[1] pg. 49-126 [1] pg. 50-99
5	The Graphical method	[1] pg. 50-99
6	The Simplex algorithm	[1] pg. 126-189
7	The Simplex algorithm	[1] pg. 126-189
8	The Simplex algorithm	[1] pg. 126-189
9	Sensitivity analysis	[1] pg. 202-294
10	Sensitivity analysis	[1] pg. 202-294
11	Midterm
12	Duality	[1] pg. 295-334
13	Duality Transportation problems	[1] pg. 295-334 [1] pg. 360-392
14	Transportation problems. Assignment and transshipment problems	[1] pg. 360-392 [1] pg. 393-412
15	Assignment and transshipment problems	[1] pg. 393-412
16	Assignment and transshipment problems	[1] pg. 393-412

Sources

Course Book	1. Winston, W.L., Operations Research: Applications and Algorithms, 4th Edition, Brooks/Cole-Thomson Learning, 2004.
Other Sources	2. Frederick S. Hillier and Gerald J. Lieberman, Introduction to Operations Research and Revised CD-ROM 8, McGraw-Hill Science, 2005.
	3. WU, N. and COPPINS, R., Linear Programming and Extensions, Cambridge University Press, 1981.
	4. Anderson D. R., Sweeney D. J., and Williams T. A., An Introduction to Management Science, 11th Edition, West, 2004.
	5. 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	5	30
Homework Assignments	-	-
Presentation	-	-
Project	-	-
Report	-	-
Seminar	-	-
Midterms Exams/Midterms Jury	1	30
Final Exam/Final Jury	1	40
Toplam	7	100

Percentage of Semester Work	60
Percentage of Final Work	40
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	Has the ability to apply scientific knowledge gained in the undergraduate education and to expand and extend knowledge in the same or in a different area
2	Can apply gained knowledge and problem solving abilities in inter-disciplinary research
3	Has the ability to work independently within research area, to state the problem, to develop solution techniques, to solve the problem, to evaluate the obtained results and to apply them when necessary
4	Takes responsibility individually and as a team member to improve systematic approaches to produce solutions in unexpected complicated situations related to the area of study
5	Can develop strategies, implement plans and principles on the area of study and can evaluate obtained results within the framework
6	Can develop and extend the knowledge in the area and to use them with scientific, social and ethical responsibility
7	Has the ability to follow recent developments within the area of research, to support research with scientific arguments and data, to communicate the information on the area of expertise in a systematically by means of written report and oral/visual presentation
8	To have an oral and written communication ability in at least one of the common foreign languages ("European Language Portfolio Global Scale", Level B2)
9	Has software and hardware knowledge in the area of expertise, and has proficient information and communication technology knowledge
10	Follows scientific, cultural, and ethical criteria in collecting, interpreting and announcing data in the research area and has the ability to teach.
11	Has professional 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	16	2	32
Application
Special Course Internship
Field Work
Study Hours Out of Class	16	4	64
Presentation/Seminar Prepration
Project
Report
Homework Assignments
Quizzes/Studio Critics	10	1	10
Prepration of Midterm Exams/Midterm Jury	1	12	12
Prepration of Final Exams/Final Jury	1	22	22
Total Workload			188