TYPE OF COURSE UNIT	Compulsory Course
LEVEL OF COURSE UNIT	Master's Degree With Thesis
YEAR OF STUDY	-
SEMESTER	-
NUMBER OF ECTS CREDITS ALLOCATED	10
NAME OF LECTURER(S)	Associate Professor Barış Keçeci
LEARNING OUTCOMES OF THE COURSE UNIT	At the end of this course, the students; 1) Know the basics of linear programming 2) Explain the solution methods of linear programming models 3) Use linear programming software and to analyze the results.
MODE OF DELIVERY	Face to face
PRE-REQUISITES OF THE COURSE	No
RECOMMENDED OPTIONAL PROGRAMME COMPONENT	None
COURSE DEFINITION	Theoretical basics of linear programming and simplex algorithm. Big M, two phase and single artificial variable methods in simplex. Duality theory, sensitivity analysis and parametric programming. Simplex for bounded variables, dual simplex, revised simplex and interior point algorithms.
COURSE CONTENTS	WEEK TOPICS 1st Week Business, Management, Scientific management, Decision making and Decision process 2nd Week Decision models, Linear decision models, Convex set 3rd Week Basic theorems of linear programming 4th Week The basis of simplex algorithm 5th Week Sufficiency of simplex algorithm / Artificial variable techniques 6th Week Special linear decision models 7th Week Duality in linear programming 8th Week Sensitivity analysis 9th Week Midterm 10th Week Degeneracy and cyclic in linear programming 11th Week Revised simplex algorithm 12th Week Bounded variable technique 13th Week Integer linear programming 14th Week Branch and bound technique
RECOMENDED OR REQUIRED READING	Kara, İ. (2000) Doğrusal Programlama, Bilim Teknik Yayınevi,İstanbul. Gass, S.I.(1975), Linear Programming, Methods and Applications, Mc-Graw-Hill Book com, New York Bazaraa M.S., Jarvis J.J., Sherali H.D., 1990, Linear Programming and Network Flows 2nd ed., John Wiley & Sons New York
PLANNED LEARNING ACTIVITIES AND TEACHING METHODS	Lecture,Questions/Answers,Problem Solving,Practice,Presentation
ASSESSMENT METHODS AND CRITERIA	Quantity Percentage(%) Mid-term 1 30 Assignment 1 5 Quiz 3 5 Practice 1 10 Attendance 1 5 Total(%) 55 Contribution of In-term Studies to Overall Grade(%) 55 Contribution of Final Examination to Overall Grade(%) 45 Total(%) 100
ECTS WORKLOAD	Activities Number Hours Workload Midterm exam 1 2 2 Preparation for Quiz 3 14 42 Individual or group work 14 10 140 Preparation for Final exam 1 25 25 Course hours 14 3 42 Preparation for Midterm exam 1 25 25 Laboratory (including preparation) 1 3 3 Final exam 1 2 2 Homework 1 14 14 Total Workload 295 Total Workload / 30 9,83 ECTS Credits of the Course 10
LANGUAGE OF INSTRUCTION	Turkish
WORK PLACEMENT(S)	No