Eskisehir Technical University Info Package Eskisehir Technical University Info Package
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About the Program Educational Objectives Key Learning Outcomes Course Structure Diagram with Credits Field Qualifications Matrix of Course& Program Qualifications Matrix of Program Outcomes&Field Qualifications
  • Faculty of Engineering
  • Department of Industrial Engineering
  • Course Structure Diagram with Credits
  • Linear Programming
  • Description
  • Description
  • Learning Outcomes
  • Course's Contribution to Prog.
  • Learning Outcomes & Program Qualifications

Course Introduction Information

Code - Course Title ENM203 - Linear Programming
Course Type Required Courses
Language of Instruction İngilizce
Laboratory + Practice 2+2
ECTS 5.5
Course Instructor(s) DOKTOR ÖĞRETİM ÜYESİ BANU İÇMEN ERDEM, PROFESÖR DOKTOR ZEHRA KAMIŞLI ÖZTÜRK
Mode of Delivery Face to face
Prerequisites Linear Algebra
Courses Recomended -
Required or Recommended Resources F. S. Hillier & G. J. Lieberman, “Introduction to Operations Research, 9/e”, McGraw Hill, 2010. • Wayne L. Winston, “Operations Research, Applications and Algorithms”, 4th Edition, Duxbury Pres Thomson Learning, Inc., 2004.• İmdat Kara, “Doğrusal Programlama”, 2. Basım, Bilim Teknik Yayınevi, İstanbul 2000.• Hamdy A. Taha, “Operations Research: An Introduction”, 8th Edition, Prentice Hall, Upper Saddle River, N.J., 2007. • DP Yazılımları (Gams, Lingo, Lindo, Winqsb, QM, Tora )
Recommended Reading List
Assessment methods and criteria 2 Midterm, 2 Quizes, 4 Homeworks, 1 Final Examination
Work Placement -
Sustainability Development Goals

Content

Weeks Topics
Week - 1 Operations Research Methodology, Basic concepts of Linear Programming
Week - 2 Formulating linear decision model, Graphical Solution, Solution techniques in LP, Assumptions of LP
Week - 3 Modeling examples with LP
Week - 4 Solving LP models with softwares (Excel and GAMS)
Week - 5 Introdcution to Simplex Algorithm, Linear Indepencendcy, Basic Solution, Relationship between Basic Feasible Solution and Extreme Point, The algebra of the Simplex Method.
Week - 6 The Simplex Method in tabular form
Week - 7 Big M Method, Two-phased Simplex Algoritm
Week - 8 Foundations of the Simplex Method
Week - 9 Revised Simplex Method
Week - 10 Duality
Week - 11 Primal-Dual relationships
Week - 12 Sensitivity analyses according to changes in model parameters
Week - 13 Sensitivity analyses according to changes in model parameters
Week - 14 The Dual Simplex Method

Learning Activities and Teaching Methods

  • Teaching Methods
  • Lecture
  • Discussion
  • Question & Answer
  • Drill - Practise
  • Problem Solving
  • Competences
  • Productive
  • Rational
  • Questoning
  • Eleştirel düşünebilme
  • Problem solving
  • Applying theoretical knowledge into practice
  • Information Management
  • Elementary computing skills
  • Decision making

Assessment Methods

Assessment Method and Passing Requirements
Quamtity Percentage (%)
1.Midterm Exam 1 30
Quiz 1 15
Homework 1 15
Final Exam 1 40
Toplam (%) 100
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