342-3362/02 – Computer Simulation of Logistics Processes I (PSLP I)
| Gurantor department | Institute of Transport | Credits | 4 |
| Subject guarantor | doc. Ing. Michal Dorda, Ph.D. | Subject version guarantor | doc. Ing. Michal Dorda, Ph.D. |
| Study level | undergraduate or graduate | Requirement | Compulsory |
| Year | 3 | Semester | winter |
| | Study language | English |
| Year of introduction | 2021/2022 | Year of cancellation | |
| Intended for the faculties | FS | Intended for study types | Bachelor |
Subject aims expressed by acquired skills and competences
The course aims to acquaint students with the methods of discrete simulation, which can be used to solve real problems in the field of logistics and planning of logistics systems. The student is acquainted with the basic theoretical principles of discrete simulation, including basic methods of statistical data processing for simulation. The student also gains practical experience working with simulation software Witness. After completing this course, the student should be able to apply these approaches to solve simple real problems in the field of logistics.
Teaching methods
Lectures
Tutorials
Summary
Discrete simulation is a robust tool for solving a number of problems in technical practice, when classical analytical methods fail. The content of the course is focused on gaining a theoretical basis for discrete simulation, as well as on gaining practical experience in creating discrete simulation models of selected problems from logistics using Witness software.
Compulsory literature:
Recommended literature:
Way of continuous check of knowledge in the course of semester
Graded credit - processing of two semester projects and a written test.
E-learning
lms.vsb.cz
Other requirements
No other requirements are defined.
Prerequisities
Subject has no prerequisities.
Co-requisities
Subject has no co-requisities.
Subject syllabus:
1) Introduction to modelling and simulation.
2) Witness simulation software – basic elements, input and output rules.
3) Witness simulation software – basic functions, probability distributions in Witness.
4) Introduction to discrete simulation.
5) Event-based algorithms.
6) Activity-based algorithms.
7) Methods of generating pseudo-random numbers.
8) Methods of transformation of pseudo-random numbers.
9) Exploratory data analysis – random sample characteristics.
10) Exploratory data analysis – large random sample processing, graphical representation.
11) Point estimation of probability distribution parameters.
12) Interval estimations of mean value.
13) Normality testing - Pearson\'s goodness-of-fit test.
14) Reserve.
Conditions for subject completion
Occurrence in study plans
Occurrence in special blocks
Assessment of instruction
Předmět neobsahuje žádné hodnocení.