Akademik Dersler - Tanıtım


Code - Course Title	ENM503 - Advanced Techniques in Linear Programming
Course Type	Required Courses
Language of Instruction	Türkçe
Laboratory + Practice	3+0
ECTS	7.5
Course Instructor(s)	DOÇENT DOKTOR NİL ARAS
Mode of Delivery	This course is conducted face to face
Prerequisites	There is no prerequisite or co-requisite for this course.
Courses Recomended	Upon completion of this course, students can take any of the following course related to mathematical programming, nonlinear programming, combinatorial optimization, heuristics, decision analysis.
Recommended Reading List
Assessment methods and criteria	1 Midterm Exam (25%) (essay exam) 1 Final Exam (40%) (essay exam) 2 Homework Assigments (20%) 1 Project (15%)
Work Placement	Students are not required to participate any field work or any other on site activities.
Sustainability Development Goals

Weeks	Topics
Week - 1	Course objectives and outlines/ The fundamental concepts of linear programming
Week - 2	Linearization techniques / Modeling with linear programming
Week - 3	Solving LP models using graphical method/ Requirement space / Fourier Motzkin method
Week - 4	Vector and matrix operations / Linear equation systems
Week - 5	Convex sets/ Convex functions/ Polyhedral sets / Polyhedral cones
Week - 6	Extreme points, faces, directions, extreme directions
Week - 7	The mathematical essentials of simplex algorithm
Week - 8	Solution with simplex algorithm / The revised simplex algorithm
Week - 9	Two-phased method / The Big-M method / Single artificial variable technique
Week - 10	Duality / Dual simplex / Interpretation of dual variables / Sensitivity analysis
Week - 11	Solution of LP models using computer softwares.
Week - 12	Farkas lemma / Karush-Kuhn-Tucker optimality conditions
Week - 13	Goal programming
Week - 14	Data envelopment analysis

Assessment Method and Passing Requirements
	Quamtity	Percentage (%)
1.Midterm Exam	1	30
Homework	1	30
Final Exam	1	40
Toplam (%)		100