M.SC. in Computer Engineering (Without Thesis)

IE 513 | Course Introduction and Application Information

Course Name

Mathematical Programming and Applications

Code	Semester	Theory (hour/week)	Application/Lab (hour/week)	Local Credits	ECTS
IE 513	Fall/Spring	3	0	3	7.5

Prerequisites	None
Course Language	English
Course Type	Elective
Course Level	Second Cycle
Mode of Delivery	-
Teaching Methods and Techniques of the Course	-
National Occupation Classification	-
Course Coordinator	Dr. Öğr. Üyesi Görkem Yılmaz
Course Lecturer(s)	Dr. Öğr. Üyesi Görkem Yılmaz
Assistant(s)	-

Course Objectives

Purpose of this course is to provide an overview of basic linear programming and discuss advanced modeling and solution techniques.

Learning Outcomes

#	Content	PC Sub	* Contribution Level
#	Content	PC Sub	1	2	3	4	5
1	Be able to formulate engineering problems as mathematical programs
2	Be able to solve mathematical problems using appropriate methods
3	Be able to apply mathematical programming and solution methods to real life problems like network flow

Course Description

Topics of this course include theory, algorithms, and computational aspects of linear programming; formulation of problems as linear programs; duality and sensitivity analysis; primaldual simplex methods; the transportation, transshipment and assignment algorithms; extensions of linear programming; integer programming formulations and solution methods.

Course Category	Core Courses
	Major Area Courses
	Supportive Courses
	Media and Management Skills Courses
	Transferable Skill Courses

WEEKLY SUBJECTS AND RELATED PREPARATION STUDIES

Week	Subjects	Related Preparation	Learning Outcome
1	Introduction to linear programming	Textbook Chapter 1
2	Geometric solution	Textbook Chapter 1
3	Linear algebra, convex analysis and polyhedral sets	Textbook Chapter 2
4	Simplex method	Textbook Chapter 3
5	Simplex method	Textbook Chapter 3
6	Simplex method	Textbook Chapter 3
7	Starting solution and convergence	Textbook Chapter 4
8	Special simplex implementations and optimality conditions	Textbook Chapter 5
9	Midterm exam
10	Duality	Textbook Chapter 6
11	Duality	Textbook Chapter 6
12	Sensitivitiy analysis	Textbook Chapter 6
13	Decomposition algorithms	Textbook Chapter 7
14	Integer Programming
15	New Year
16	Review of the Semester

Course Notes/Textbooks	Introduction to operations research. Hillier, F. S., & Lieberman, G. J., 10th edition, 2015, McGraw-Hill.
Suggested Readings/Materials	Linear programming and network flows. Bazaraa, M. S., Jarvis, J. J., & Sherali, H. D., 4th edition, 2011, John Wiley & Sons. Operations research: applications and algorithm. Winston, W. L., 4th edition, 2004, Thomson Learning.

EVALUATION SYSTEM

Semester Activities	Number	Weighting	LO 1	LO 2	LO 3
Participation
Laboratory / Application
Field Work
Quizzes / Studio Critiques
Portfolio
Homework / Assignments		20
Presentation / Jury
Project	1	15
Seminar / Workshop
Oral Exams
Midterm	1	25
Final Exam	1	40
Total

Weighting of Semester Activities on the Final Grade	3	60
Weighting of End-of-Semester Activities on the Final Grade	1	40
Total

ECTS / WORKLOAD TABLE

Semester Activities	Number	Duration (Hours)	Workload
Theoretical Course Hours (Including exam week: 16 x total hours)	16	3	48
Laboratory / Application Hours (Including exam week: '.16.' x total hours)	16		0
Study Hours Out of Class	14	6	84
Field Work			0
Quizzes / Studio Critiques			0
Portfolio			0
Homework / Assignments			0
Presentation / Jury			0
Project	1	33	33
Seminar / Workshop			0
Oral Exam			0
Midterms	1	25	25
Final Exam	1	35	35
		Total	225

COURSE LEARNING OUTCOMES AND PROGRAM QUALIFICATIONS RELATIONSHIP

#	PC Sub	Program Competencies/Outcomes	* Contribution Level
#	PC Sub	Program Competencies/Outcomes	1	2	3	4	5
1	Accesses information in breadth and depth by conducting scientific research in Computer Engineering, evaluates, interprets and applies information.		-	-	-	X	-
2	Is well-informed about contemporary techniques and methods used in Computer Engineering and their limitations.		-	-	-	-	X
3	Uses scientific methods to complete and apply information from uncertain, limited or incomplete data, can combine and use information from different disciplines.		-	-	-	X	-
4	Is informed about new and upcoming applications in the field and learns them whenever necessary.		-	-	-	-	X
5	Defines and formulates problems related to Computer Engineering, develops methods to solve them and uses progressive methods in solutions.		-	-	-	-	X
6	Develops novel and/or original methods, designs complex systems or processes and develops progressive/alternative solutions in designs.		-	-	-	-	X
7	Designs and implements studies based on theory, experiments and modelling, analyses and resolves the complex problems that arise in this process.		-	-	-	X	-
8	Can work effectively in interdisciplinary teams as well as teams of the same discipline, can lead such teams and can develop approaches for resolving complex situations, can work independently and takes responsibility.		-	-	-	-	X
9	Engages in written and oral communication at least in Level B2 of the European Language Portfolio Global Scale.		-	-	X	-	-
10	Communicates the process and the results of his/her studies in national and international venues systematically, clearly and in written or oral form.		-	-	X	-	-
11	Is knowledgeable about the social, environmental, health, security and law implications of Computer Engineering applications, knows their project management and business applications, and is aware of their limitations in Computer Engineering applications.		-	-	X	-	-
12	Highly regards scientific and ethical values in data collection, interpretation, communication and in every professional activity.		-	X	-	-	-