Master
2022/2023
Applied Quantitative Logistics
Type:
Elective course (Data Science)
Area of studies:
Applied Mathematics and Informatics
Delivered by:
School of Data Analysis and Artificial Intelligence
Where:
Faculty of Computer Science
When:
1 year, 3, 4 module
Mode of studies:
offline
Open to:
students of one campus
Master’s programme:
Data Science
Language:
English
ECTS credits:
6
Contact hours:
56
Course Syllabus
Abstract
This course covers chapters from Discrete Mathematics, Game Theory, and Epistemic Logics to find market equilibriums and handle uncertainty. Programming skills are very important for this course. It also includes basic quantitative logistics models and algorithms for Allocation, Transportation, and Vehicle Routing Problems including the sensitivity and stability analysis applied to the Minimum Spanning Tree Problem (MSTP) and its variations, Shortest Path, Traveling Salesman and Vehicle Routing Problems (Capacitated, Time Windows, Pick Up and Delivery, etc.), Preempted Single Machine Scheduling Jobs (Operations) with Arbitrary Processing Times, Release and Due Dates will be studied in this course.