PAÜ .:. Eğitim Öğretim Bilgi Sistemi

COURSE INFORMATION

Course Code	Course Title	L+P Hour	Semester	ECTS
MUHY 576	OPTIMIZATION TECHNICS	3 + 0	2nd Semester	6

COURSE DESCRIPTION

Course Level	Doctorate 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

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

	Course Term	No	Instructors
Details	2016-2017 Spring	1	ÖZCAN MUTLU
Details	2015-2016 Spring	1	ÖZCAN MUTLU

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

Prospective Student