COURSE UNIT TITLE

: DECISION ANALYSIS AND MODELS

Description of Individual Course Units

Course Unit Code Course Unit Title Type Of Course D U L ECTS
BIS 5005 DECISION ANALYSIS AND MODELS ELECTIVE 3 0 0 5

Offered By

Business Information Systems (English)

Level of Course Unit

Second Cycle Programmes (Master's Degree)

Course Coordinator

ASSOCIATE PROFESSOR GÜZIN ÖZDAĞOĞLU

Offered to

Business Information Systems (English)
Business Administration (English)

Course Objective

This course provides a framework for analyzing decisions made by business firms. Focus is on management science tools and decision making approaches that are widely used to formulate strategies for business-oriented optimization problems.

Learning Outcomes of the Course Unit

1   Have a knowledge understanding of the basic elements of Mathematical Programming, including the decision variables, the objective function, and the constraints,
2   Have a knowledge understanding of the graphical solution to Linear Programming problems,
3   Perform sensitivity analysis and understand the information it conveys,
4   Develop applications to optimize the real world business problems,
5   Be able to use Spreadsheet Software and a solver to solve and analyze optimization problems.

Mode of Delivery

Face -to- Face

Prerequisites and Co-requisites

None

Recomended Optional Programme Components

None

Course Contents

Week Subject Description
1 Decision Process and Model Building Lecture
2 Decision Theory and Utility Decision Making Under Uncertainty and Risk Lecture
3 Introduction to Linear Programming (LP) Lecture +Computer Lab Applications
4 Solving LP models using spreadsheets for optimization. Sensitivity Analysis Lecture + Computer Lab Applications
5 Solving LP models using spreadsheets for optimization. Sensitivity Analysis Lecture + Computer Lab Applications
6 Integer Programming Lecture + Computer Lab Applications
7 Integer Programming Lecture + Computer Lab Applications
8 Midterm Exam
9 Multiobjective Programming Lecture + Computer Lab Applications
10 Multiobjective Programming Lecture + Computer Lab Applications
11 Network optimization Lecture + Computer Lab Applications
12 Network optimization Lecture + Computer Lab Applications
13 Nonlinear optimization Lecture + Computer Lab Applications
14 Nonlinear optimization Lecture + Computer Lab Applications
15 Case Study Presentations Submission of Case Analysis Reports

Recomended or Required Reading

Text Books:
-Management Science Modelling- Wayne L. Winston (Alternatively Practical Management Science, Wayne L. Winston)
- Operations Research: Applications and Algorithms, Wayne L. Winston, 4th ed. or later ed., Thomson Learning.
- Decision Theory, Principles and Applications, Giovanni Parmigiani, Lurdes Yoshiko Tani Inoue, John Wiley and Sons, 2009
Software:
- Spreadsheet Software with Solver add-in.

Planned Learning Activities and Teaching Methods

1. Lectures
2. Review Sessions and Class Discussions
3. Computer Applications
4. Case Studies

Assessment Methods

SORTING NUMBER SHORT CODE LONG CODE FORMULA
1 MTE MIDTERM EXAM
2 STT TERM WORK (SEMESTER)
3 FIN FINAL EXAM
4 FCG FINAL COURSE GRADE MTE * 0.30 + STT * 0.30 + FIN* 0.40
5 RST RESIT
6 FCGR FINAL COURSE GRADE (RESIT) MTE * 0.30 + STT * 0.30 + RST* 0.40


*** Resit Exam is Not Administered in Institutions Where Resit is not Applicable.

Further Notes About Assessment Methods

None

Assessment Criteria

Grade for Student Participation will depend on (i) class attendance, (ii) the quality of the answers student provide to questions posed by the instructor during class, and (iii) the general contribution the student make to the creation of a positive learning environment.

A good attendance record will bring the grade up one level, for grades on the boundary between two grade levels.

The case analysis requires a systematic and analytic thinking to integrate all business functions and formulate strategies that will enable businesses to succeed in the business environment. It is the responsibility of the student to contribute to class discussions actively. The contribution will be evaluated for such factors as apparent understanding of the topic, originality and clarity of discussion, comprehensiveness of the solution strategy formulated.

Language of Instruction

English

Course Policies and Rules

1. It is obligatory to attend at least 70% of the classes.
2. Plagiarism of any kind will result in disciplinary steps being taken.
3. Absence will not be considered an excuse for submitting homework assignments late.
4. Delayed case reports will suffer grade decay equivalent to one letter grade per day late.

Contact Details for the Lecturer(s)

guzin.kavrukkoca@deu.edu.tr

Office Hours

To be announced at the first lecture.

Work Placement(s)

None

Workload Calculation

Activities Number Time (hours) Total Work Load (hours)
Lectures 13 3 39
Preparation for final exam 1 20 20
Preparation for midterm exam 1 20 20
Preparations before/after weekly lectures 10 1,5 15
Preparing presentations 1 5 5
Preparing assignments 8 3 24
Midterm 1 3 3
Final 1 3 3
TOTAL WORKLOAD (hours) 129

Contribution of Learning Outcomes to Programme Outcomes

PO/LOPO.1PO.2PO.3PO.4PO.5PO.6PO.7
LO.1555
LO.24545
LO.355
LO.45555
LO.5555