At the end of this course, the students; 1) Develop the infrastructure necessary to distinguish the best model appropriate for a specific decision making situation and develop skills for formulating mathematical models of real life business problems. 2) Introduce the solution methodologies and introduce spreadsheets or other specialized software available to solve the models. 3) Develop skills for analyzing and interpreting the results of the computer output in order to recommend appropriate courses of action. 4) At the end of this course the student will demonstrate the ability to approach different kinds of decision making situations analytically and interpret the results obtained by various quantitative techniques. 5) Learn, through case studies, the applications of Management Science to find solutions to real life business problems including those in global environment. 6) Develop analytical skills in structuring and analysis (scientific method) of business decision problems which characterize the field of Management Science.
MODE OF DELIVERY
Face to face
PRE-REQUISITES OF THE COURSE
No
RECOMMENDED OPTIONAL PROGRAMME COMPONENT
None
COURSE DEFINITION
In this course, the emergence of Science in Management, scope and importance of the field of management quantitative decision techniques and applications will be covered. Linear Programming Models will be introduced and solution techniques, sensitivity analysis will be discussed. In addition, the special types of linear programming: Assignment, Transportation and Integer Programming models, Decision Theory, Network Models, Project Planning Techniques (PERT / CPM) and the waiting line models and simulation will be examined.
COURSE CONTENTS
WEEK
TOPICS
1st Week
Linear Programming: Model Formulation
2nd Week
Linear Programming: Graphical Solution
3rd Week
Linear Programming:Sensitivity Analysis of Objective Function Values
4th Week
Linear Programming Computer Applications
5th Week
Transportation Problem
6th Week
Assignment Problem
7th Week
Integer Linear Programming
8th Week
Midterm Exam
9th Week
Decision Analysis
10th Week
Network Modeling
11th Week
Project Management
12th Week
Queueing Modeling
13th Week
Simulation
14th Week
Computer Applications of Queueing Theory and Simulation
RECOMENDED OR REQUIRED READING
Balakrishnan, N., B. Render, and R. M. Stair Jr. 2007. Managerial Decision Modeling with Spreadsheets. Upper Saddle River, New Jersey: Prentice-Hall, Incorporated. Taylor, Bernard W. 2001. Introduction to Management Science 7th Ed., Prentice Hall. Hillier, F.S., Lieberman, G.J. 1995. Introduction to Operations Research 6th Ed., McGraw-Hill. Acar, A. 1998. Linear Programming For Managerial Decisions 3rd Ed., METU. Anderson, D. R., D. J. Sweeney ve T. W. Williams. 2000. In Introduction to Management Science: Quantitative Approaches to Decision Making. South Western Collage Publishing. Winston, W. L. 1994. Operations Research: Applications and Algorithms 3rd Ed. Duxbury Press. Lawrence, Jr. J.A and B.A Posternock, 1998. Applied Management Science A Computer Integrated Approach for Decision Making, John Wiley and Sons, New York.
PLANNED LEARNING ACTIVITIES AND TEACHING METHODS
Lecture,Problem Solving
ASSESSMENT METHODS AND CRITERIA
Quantity
Percentage(%)
Mid-term
1
30
Quiz
1
25
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
3
3
Preparation for Quiz
1
4
4
Individual or group work
14
5
70
Preparation for Final exam
1
45
45
Course hours
14
3
42
Preparation for Midterm exam
1
35
35
Laboratory (including preparation)
Final exam
1
4
4
Homework
Quiz
1
,5
,5
Total Workload
203,5
Total Workload / 30
6,78
ECTS Credits of the Course
7
LANGUAGE OF INSTRUCTION
Turkish
WORK PLACEMENT(S)
No
KEY LEARNING OUTCOMES (KLO) / MATRIX OF LEARNING OUTCOMES (LO)
