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)
Mode of Delivery	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: 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	There is no work placement offered on this course.
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 (%)
Toplam (%)		0