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SECOND CYCLE - MASTER'S DEGREE
THE GRADUATE SCHOOL OF NATURAL AND APPLIED SCIENCES
INDUSTRIAL ENGINEERING DEPARTMENT
1265 ENGINEERING MANAGEMENT( Without Thesis)
Course Information
Course Learning Outcomes
Course's Contribution To Program
ECTS Workload
Course Details
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COURSE INFORMATION
Course Code
Course Title
L+P Hour
Semester
ECTS
MUHY 576
OPTIMIZATION TECHNICS
3 + 0
2nd Semester
6
COURSE DESCRIPTION
Course Level
Master's Degree
Course Type
Elective
Course Objective
In this course the modelling of real life optimization problems and their solutions methods are examined in detail
Course Content
Linear programming problems, integer programming problems, knapsack problems, location allocation problems, assembly line balancing problems, traveling salesman problems, scheduling problems
Prerequisites
No the prerequisite of lesson.
Corequisite
No the corequisite of lesson.
Mode of Delivery
Face to Face
COURSE LEARNING OUTCOMES
1
Understand the concept of modelling
2
Models the real life problems
3
Solve the models by using GAMS
COURSE'S CONTRIBUTION TO PROGRAM
PO 01
PO 02
PO 03
PO 04
PO 05
PO 06
PO 07
PO 08
PO 09
PO 10
LO 001
LO 002
LO 003
Sub Total
Contribution
0
0
0
0
0
0
0
0
0
0
ECTS ALLOCATED BASED ON STUDENT WORKLOAD BY THE COURSE DESCRIPTION
Activities
Quantity
Duration (Hour)
Total Work Load (Hour)
Course Duration (14 weeks/theoric+practical)
14
3
42
Hours for off-the-classroom study (Pre-study, practice)
14
5
70
Mid-terms
1
20
20
Final examination
1
24
24
Total Work Load
ECTS Credit of the Course
156
6
COURSE DETAILS
Select Year
All Years
2016-2017 Spring
2015-2016 Spring
2014-2015 Spring
Course Term
No
Instructors
Details
2016-2017 Spring
1
ÖZCAN MUTLU
Details
2015-2016 Spring
1
ÖZCAN MUTLU
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Course Details
Course Code
Course Title
L+P Hour
Course Code
Language Of Instruction
Course Semester
MUHY 576
OPTIMIZATION TECHNICS
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 the modelling of real life optimization problems and their solutions methods are examined in detail
Content
Linear programming problems, integer programming problems, knapsack problems, location allocation problems, assembly line balancing problems, traveling salesman problems, scheduling problems
Topics
Weeks
Topics
1
Basic concepts
2
Linear programming (LP) problems
3
LP aplications
4
LP aplications
5
Simplex algorithm
6
Simplex algorithm
7
Big M and thw phase method
8
Duality and dual simplex algorithm
9
Duality and dual simplex algorithm
10
Midterm exam
11
Sensitivity analysis
12
Transportation problems
13
Transportation problems
14
Assignment problems
Materials
Materials are not specified.
Resources
Resources
Resources Language
Operations Research Applications and Algorithms Wayne L. Winston, PWS-Kent Publishing Company
English
Yöneylem Araştırması, Hamdi Taha, Literatür Yayınları
Türkçe
Course Assessment
Assesment Methods
Percentage (%)
Assesment Methods Title
Final Exam
50
Final Exam
Midterm Exam
50
Midterm Exam
L+P:
Lecture and Practice
PQ:
Program Learning Outcomes
LO:
Course Learning Outcomes
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Home Page
About University
Name And Address
Acedemic Authorities
General Discription
Academic Calendar
General Admission Requirements
Recognition of Prior Learning
General Registration Procedures
ECTS Credit Allocation
Academic Guidance
Information For Students
Cost Of Living
Accommodation
Meals
Medical Facilities
Facilities for Special Needs Students
Insurance
Financial Support for Students
Student Affairs
Learning Facilities
International Programs
Language Courses
Internships
Sports Facilities and Leisure Activities
Student Associations
Practical Information for Mobile Students
Degree Programmes