To teach basics of linear programming models and solution techniques, how to apply the models to different business problems, network models and their application areas.
20
Contribution of the Course to Professional Development
21
Learning Outcomes:
1
To know how to design linear programming models;
2
To understand the solution methods of linear programming;
3
To create and solve Linear Programming Models for managerial problems as production planning, logistics, human resources and etc;
4
To create and solve linear Programming Models for finance and investment problems;
5
To interpret results of the models and do Sensitivity Analysis;
6
To comprehend fundamentals of Network Analysis;
7
To apply Network Models to financial planning problems, to interpret results of the models and making risk analysis;
22
Course Content:
Week
Theoretical
Practical
1
Basic principles and the structure of Linear Programming Models
2
To create profit and cost optimization models for production planning and business management problems
3
To create Linear Programming Models for financial and investment planning problems
4
Graphic Method and Simplex Algorithm for Linear Programming
5
To solve and make economic interpretation of the results of business and finance problems
6
To comprehend Sensitivity Analysis and Parametric Programming and to apply these approaches to finance problems
7
To solve Linear Programming Models with Excel Solver, to make economic interpretations of the results
8
To solve and interpret the results of business and finance problems in the context of economics and to make a Sensitivity Analysis
9
Time Value of money and Annuity Method
10
Risk and Sensitivity Analysis in investment project evaluations
11
Fundamentals of Network Analysis
12
Critical Path Method and its applications
13
Project Evaluation and Review Technique and its applications
14
Optimization in resource levelling
23
Textbooks, References and/or Other Materials:
Wayne Winston, Operations Research Aydın Ulucan, Yöneylem Araştırması H.Tütek/Ş.Gümüşoğlu, Sayısal Yöntemler (Yönetsel Yaklaşım)
24
Assesment
TERM LEARNING ACTIVITIES
NUMBER
PERCENT
Midterm Exam
0
0
Quiz
0
0
Homeworks, Performances
1
40
Final Exam
1
60
Total
2
100
Contribution of Term (Year) Learning Activities to Success Grade
40
Contribution of Final Exam to Success Grade
60
Total
100
Measurement and Evaluation Techniques Used in the Course
Information
25
ECTS / WORK LOAD TABLE
Activites
NUMBER
TIME [Hour]
Total WorkLoad [Hour]
Theoretical
14
3
42
Practicals/Labs
0
0
0
Self Study and Preparation
14
3
42
Homeworks, Performances
1
60
60
Projects
0
0
0
Field Studies
0
0
0
Midtermexams
0
0
0
Others
0
0
0
Final Exams
1
35
35
Total WorkLoad
179
Total workload/ 30 hr
5,97
ECTS Credit of the Course
6
26
CONTRIBUTION OF LEARNING OUTCOMES TO PROGRAMME QUALIFICATIONS
