TYPE OF COURSE UNIT	Elective Course
LEVEL OF COURSE UNIT	Doctorate Of Science
YEAR OF STUDY	-
SEMESTER	-
NUMBER OF ECTS CREDITS ALLOCATED	15
NAME OF LECTURER(S)	-
LEARNING OUTCOMES OF THE COURSE UNIT	At the end of this course, the students; 1) Use various linear programming methods to make good decisions. 2) Develop the infrastructure necessary to distinguish the best model appropriate for a specific decision making situation. 3) Develop skills for formulating mathematical models of real life business problems. 4) Use specialized software available to solve the models. 5) Develop skills for interpreting the results of the computer outputs. 6) Demonstrate the ability to approach different kinds of decision making situations analytically. 7) Develop analytical skills in structuring and analysis of business decision problems that display characteristics of linearity.
MODE OF DELIVERY	Face to face
PRE-REQUISITES OF THE COURSE	No
RECOMMENDED OPTIONAL PROGRAMME COMPONENT	MAND618 MANAGERIAL DECISION MAKING
COURSE DEFINITION	The field of linear programming aims to solve organizations' problems via mathematical expressions. This course includes quantifying problems faced by firms and producing optimal solutions for those quantified problems. mathematical expression
COURSE CONTENTS	WEEK TOPICS 1st Week Fundamentals of Linear Programming 2nd Week Formulating the Linear Programming Models: Business Applicatiions 3rd Week Solving the Linear Programming Problems: Graphical and Computer Methods 4th Week Spacial Types of Linear Programming Problems 5th Week Sensitivity Analysis of the Objective Function Coefficients, Ranges of Optimality and Reduced Costs 6th Week Sensitivity Analysis of the Right-Hand Side Values (Shadow Prices) and Ranges of Validity 7th Week Use of Sensitivity Analysis in Decision Making with Managerial Applications 8th Week Midterm 9th Week Network Flow Formulations (the Transportation, the Transshipment and Assignment Models) 10th Week Network Flow Formulations (the Maximum Flow, Minimum Spanning Tree, Shortest Route, Traveling Salesman Models) 11th Week Goal Programming Formulations 12th Week Integer Linear Programming Formulations with General Integer Variables 13th Week Integer Linear Programming Formulations with Binary Decision Variables 14th Week Business Applications
RECOMENDED OR REQUIRED READING	Taylor, Bernard W. 2012. Introduction to Management Science, 11.thed., Pearson.
PLANNED LEARNING ACTIVITIES AND TEACHING METHODS	Lecture,Discussion
ASSESSMENT METHODS AND CRITERIA	Quantity Percentage(%) Mid-term 1 30 Quiz 1 20 Total(%) 50 Contribution of In-term Studies to Overall Grade(%) 50 Contribution of Final Examination to Overall Grade(%) 50 Total(%) 100
ECTS WORKLOAD	Activities Number Hours Workload Midterm exam 1 2 2 Preparation for Quiz 2 8 16 Individual or group work 13 6 78 Preparation for Final exam 1 170 170 Course hours 14 3 42 Preparation for Midterm exam 1 80 80 Laboratory (including preparation) 1 40 40 Final exam 1 2 2 Homework 4 4 16 Article Total Workload 446 Total Workload / 30 14,86 ECTS Credits of the Course 15
LANGUAGE OF INSTRUCTION	Turkish
WORK PLACEMENT(S)	No