1. SECOND CYCLE - MASTER'S DEGREE
  2. THE GRADUATE SCHOOL OF NATURAL AND APPLIED SCIENCES
  3. INDUSTRIAL ENGINEERING DEPARTMENT
  4. 1261 Industrial Engineering
Course Information Course Learning Outcomes Course's Contribution To Program ECTS Workload Course Details
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COURSE INFORMATION
Course CodeCourse TitleL+P HourSemesterECTS
ENM 506OPTIMIZATION TECHNICS II3 + 02nd Semester7,5

COURSE DESCRIPTION
Course Level Master's Degree
Course Type Elective
Course Objective In this course, advance topics in linear and nonlinear programming will be discussed.
Course Content Basic concepts in linear programming, duality, interior point algorithm, constraint and nonconstraint nonlinear programming, quadratic programming, Lagrange relaxation, optimization algorithms.
Prerequisites No the prerequisite of lesson.
Corequisite No the corequisite of lesson.
Mode of Delivery Face to Face

COURSE LEARNING OUTCOMES
1Understands fundamental theorems
2Models and solves non-linear programming problems
3Learns optimization algorithms

COURSE'S CONTRIBUTION TO PROGRAM
PO 01PO 02PO 03PO 04PO 05PO 06PO 07PO 08PO 09PO 10
LO 0015522211115
LO 0023322211115
LO 0032211111115
Sub Total1010555333315
Contribution3322211115

ECTS ALLOCATED BASED ON STUDENT WORKLOAD BY THE COURSE DESCRIPTION
ActivitiesQuantityDuration (Hour)Total Work Load (Hour)
Course Duration (14 weeks/theoric+practical)14342
Assignments4520
Mid-terms16060
Final examination17373
Total Work Load

ECTS Credit of the Course





195

7,5
COURSE DETAILS
 Select Year   


 Course TermNoInstructors
Details 2016-2017 Spring1ÖZCAN MUTLU
Details 2012-2013 Spring1ÖZCAN MUTLU
Details 2009-2010 Spring1ÖZCAN MUTLU


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Course Details
Course Code Course Title L+P Hour Course Code Language Of Instruction Course Semester
ENM 506 OPTIMIZATION TECHNICS II 3 + 0 1 Turkish 2016-2017 Spring
Course Coordinator  E-Mail  Phone Number  Course Location Attendance
Assoc. Prof. Dr. ÖZCAN MUTLU mutlu@pau.edu.tr MUH A0457 %
Goals In this course, advance topics in linear and nonlinear programming will be discussed.
Content Basic concepts in linear programming, duality, interior point algorithm, constraint and nonconstraint nonlinear programming, quadratic programming, Lagrange relaxation, optimization algorithms.
Topics
WeeksTopics
1 Goal programming
2 Goal programming
3 Goal programming
4 Data Envelopment Analysis
5 Data Envelopment Analysis
6 Data Envelopment Analysis
7 Game Theory
8 Game Theory
9 Mid Term
10 Non-linear programming
11 Non-linear programming
12 Dynamic programming
13 Dynamic programming
14 Presentations
Materials
Materials are not specified.
Resources
ResourcesResources Language
1. Operations Research Applications and Algorithms Wayne L. Winston, PWS-Kent Publishing CompanyEnglish
2. Yöneylem Araştırması, Hamdi Taha, Literatür YayınlarıTürkçe
3. Ders notlarıTürkçe
Course Assessment
Assesment MethodsPercentage (%)Assesment Methods Title
Final Exam50Final Exam
Midterm Exam50Midterm Exam
L+P: Lecture and Practice
PQ: Program Learning Outcomes
LO: Course Learning Outcomes