Akademik Dersler - Tanıtım


Code - Course Title	ENM452 - Introduction to Multiobjective Optimization
Course Type	Area Elective Courses
Language of Instruction	İngilizce
Laboratory + Practice	3+0
ECTS	5.0
Course Instructor(s)	DOÇENT DOKTOR GÜLÇİN DİNÇ YALÇIN
Mode of Delivery	Face to face
Prerequisites	ENM 203 Lineer Programming
Courses Recomended	-
Required or Recommended Resources	• Gabriele Eichfelder, Adaptive Scalarization Methods in Multiobjective Optimization.• Wayne Winston, Operations Research Applications and Algorithms, 4th edition: 4. Bölüm. The Simplex Algorithm and Goal Programming.• Kasimbeyli R., Kamisli Ozturk, Z., Kasimbeyli N., Dinc Yalcin, G. ve Icmen, B., (2019) “Comparison of Some Scalarization Methods in Multiobjective Optimization” Bulletin of the Malaysian Mathematical Sciences Society, 42(5), 1875-1905, Doi: https://doi.org/10.1007/s40840-017-0579-4.
Recommended Reading List	-
Assessment methods and criteria	Exam , project
Work Placement	-
Sustainability Development Goals

Weeks	Topics
Week - 1	Introduction to multiobjective optimization
Week - 2	Decision variables space, purposes space, order relations and examples
Week - 3	Weighted Sum Method
Week - 4	ϵ-Constrained Method
Week - 5	Benson Method
Week - 6	Benson Method
Week - 7	Benson Method
Week - 8	Chebyshev Scalarization Method
Week - 9	Pascoletti–Serafini Scalarization Method
Week - 10	Conic Scalarization Method
Week - 11	Conic Scalarization Method
Week - 12	Goal Programming
Week - 13	Application of Methods to an Industrial Engineering Problem
Week - 14	Application of Methods to an Industrial Engineering Problem

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