TYPE OF COURSE UNIT	Compulsory Course
LEVEL OF COURSE UNIT	Doctorate Of Science
YEAR OF STUDY	-
SEMESTER	-
NUMBER OF ECTS CREDITS ALLOCATED	10
NAME OF LECTURER(S)	Professor İmdat Kara
LEARNING OUTCOMES OF THE COURSE UNIT	At the end of this course, the students; 1) Know the basics of combinatorial optimization 2) Explain and use the solution methods of combinatorial optimization models
MODE OF DELIVERY	Face to face
PRE-REQUISITES OF THE COURSE	No
RECOMMENDED OPTIONAL PROGRAMME COMPONENT	None
COURSE DEFINITION	Defining and modeling the combinatorial problems in Industrial Engineering; analysis of algorithms and solution methods specific to these kind of problems.
COURSE CONTENTS	WEEK TOPICS 1st Week Combinatorial problems and integer programming. 2nd Week NP-hard problem type 3rd Week Branch and Bound algorithm 4th Week Branch and Bound algorithm 5th Week Branch and cut algorithm 6th Week Branch and cut algorithm 7th Week Branch and cut algorithm 8th Week MIDTERM 9th Week Branch and price algorithm 10th Week Branch and price algorithm 11th Week Greedy algorithm 12th Week Greedy algorithm 13th Week Edmond algorithm 14th Week Matroids
RECOMENDED OR REQUIRED READING	Moustapha Diaby, Mark H. Karwan, Advances in Combinatorial Optimization
PLANNED LEARNING ACTIVITIES AND TEACHING METHODS	Presentation
ASSESSMENT METHODS AND CRITERIA	Quantity Percentage(%) Mid-term 1 35 Project 1 35 Total(%) 70 Contribution of In-term Studies to Overall Grade(%) 70 Contribution of Final Examination to Overall Grade(%) 30 Total(%) 100
ECTS WORKLOAD	Activities Number Hours Workload Midterm exam 1 2 2 Preparation for Quiz Individual or group work 14 14 196 Preparation for Final exam 1 25 25 Course hours 14 3 42 Preparation for Midterm exam 1 25 25 Laboratory (including preparation) Final exam 1 2 2 Homework 1 14 14 Total Workload 306 Total Workload / 30 10,2 ECTS Credits of the Course 10
LANGUAGE OF INSTRUCTION	Turkish
WORK PLACEMENT(S)	No