Master Program in Logistics and Financial Management

Simulation with Applications in Logistics(LFM 521)

Course Code Course Name Semester Theory Practice Lab Credit ECTS
LFM 521 Simulation with Applications in Logistics 2 3 0 0 3 6
Prerequisites
Admission Requirements
Language of Instruction English
Course Type Compulsory
Course Level Masters Degree
Course Instructor(s) EBRU ANGÜN ebru.angun@gmail.com (Email)
Assistant
Objective Simulation is a statistical computer-based technique to model and analyze complex, real-life problems. This course aims at enabling students to model real-life logistics problems through simulation models, estimate several performance measures through statistical analysis, analyze the sensitivity of the system to various parameters, and find the optimum operating conditions. The objectives of the course are determined as follows:
• Introduce how to build simulation models of real-life problems
• Enable students to use the statistical techniques efficiently
• Enable students to use softwares such ARENA and MATLAB efficiently and effectively
• Enable students to use sensitivity analysis and simulation-based optimization techniques
Content
Course Learning Outcomes Upon successful completion of this course, the student will be able to
LO 1: Build ARENA model of a real-life logistics problem.
LO 2: Distinguish different types of simulation and how they are used.
LO 3: Perform input analysis through various statistical procedures.
LO 4: Interpret the results of statistical packages.
LO 5: Explain how computers generate uniform pseudo-variates.
LO 6: Compare and test different pseudo-random number generators in different softwares (e.g., MATLAB)
LO 7: Define several methods to generate random variates.
LO 8: Define different techniques for the output analysis for different types of simulation.
LO 9: Define classic and new methods for design of experiments.
LO 10: Perform simulation-optimization techniques and obtain optimum operating conditions.
LO 11: Perform sensitivity analysis and find the most important parameters fort he system.
Teaching and Learning Methods
References Law, A.M., “Simulation Modeling and Analysis”, 4. Edition, McGraw-Hill, New York, 2007
Kelton, W.D., Sadowski, R.P., Sturrock, D.T., “Simulation with ARENA”, 3. Edition, McGraw-Hill, New York, 2003
Kleijnen, J.P.C., “Design and Analysis of Simulation Experiments”, Springer, New York, 2008
Alexopoulos, C., Seila, A., “Output data analysis”, Chapter 7 in Handbook of Simulation, Wiley, New York, 1998
Print the course contents
Theory Topics
Week Weekly Contents
Practice Topics
Week Weekly Contents
Contribution to Overall Grade
  Number Contribution
Contribution of in-term studies to overall grade 2 60
Contribution of final exam to overall grade 1 40
Toplam 3 100
In-Term Studies
  Number Contribution
Assignments 0 0
Presentation 0 0
Midterm Examinations (including preparation) 1 30
Project 1 30
Laboratory 0 0
Other Applications 0 0
Quiz 0 0
Term Paper/ Project 0 0
Portfolio Study 0 0
Reports 0 0
Learning Diary 0 0
Thesis/ Project 0 0
Seminar 0 0
Other 0 0
Toplam 2 60
No Program Learning Outcomes Contribution
1 2 3 4 5
1
2
3 X
4 X
5
6
7
8 X
9
10
11 X
12 X
13 X
14 X
15
Activities Number Period Total Workload
Class Hours 14 3 42
Working Hours out of Class 13 2 26
Assignments 3 7 21
Midterm Examinations (including preparation) 1 15 15
Project 1 40 40
Final Examinations (including preparation) 1 17 17
Total Workload 161
Total Workload / 25 6.44
Credits ECTS 6
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