040186 KU Transportation Logistics (MA) (2020S)
Continuous assessment of course work
Labels
The course language is English.Only students who signed up for the class in univis/u:space are allowed to take the class (that means, that you have to at least be on the waiting list if you want to take this class). No exceptions possible.
Registration/Deregistration
Note: The time of your registration within the registration period has no effect on the allocation of places (no first come, first served).
- Registration is open from Mo 10.02.2020 09:00 to We 19.02.2020 12:00
- Registration is open from Tu 25.02.2020 09:00 to We 26.02.2020 12:00
- Deregistration possible until Th 30.04.2020 23:59
Details
max. 50 participants
Language: English
Lecturers
Classes (iCal) - next class is marked with N
Wednesday
04.03.
11:30 - 13:00
Hörsaal 7 Oskar-Morgenstern-Platz 1 1.Stock
Wednesday
11.03.
11:30 - 13:00
Hörsaal 7 Oskar-Morgenstern-Platz 1 1.Stock
Wednesday
18.03.
11:30 - 13:00
Hörsaal 7 Oskar-Morgenstern-Platz 1 1.Stock
Wednesday
25.03.
11:30 - 13:00
Hörsaal 7 Oskar-Morgenstern-Platz 1 1.Stock
Wednesday
01.04.
11:30 - 13:00
Hörsaal 7 Oskar-Morgenstern-Platz 1 1.Stock
Wednesday
22.04.
11:30 - 13:00
Hörsaal 7 Oskar-Morgenstern-Platz 1 1.Stock
Wednesday
29.04.
11:30 - 13:00
Hörsaal 7 Oskar-Morgenstern-Platz 1 1.Stock
Wednesday
06.05.
11:30 - 13:00
Hörsaal 7 Oskar-Morgenstern-Platz 1 1.Stock
Wednesday
13.05.
11:30 - 13:00
Hörsaal 7 Oskar-Morgenstern-Platz 1 1.Stock
Wednesday
20.05.
11:30 - 13:00
Hörsaal 7 Oskar-Morgenstern-Platz 1 1.Stock
Wednesday
27.05.
11:30 - 13:00
Hörsaal 7 Oskar-Morgenstern-Platz 1 1.Stock
Wednesday
03.06.
11:30 - 13:00
Hörsaal 7 Oskar-Morgenstern-Platz 1 1.Stock
Wednesday
10.06.
11:30 - 13:00
Hörsaal 7 Oskar-Morgenstern-Platz 1 1.Stock
Wednesday
17.06.
11:30 - 13:00
Hörsaal 7 Oskar-Morgenstern-Platz 1 1.Stock
Wednesday
24.06.
11:30 - 13:00
Hörsaal 7 Oskar-Morgenstern-Platz 1 1.Stock
Information
Aims, contents and method of the course
This course is an introduction to some optimisation problems that appear in Transportation Logistics. Along the semester, we will cover several of these problems, and study their corresponding mathematical formulations and solution methods.Among the problems we will study: classical network problems (minimum spanning tree, shortest paths, maximum flows), warehouse location problem and its capacitated version, transportation problem, assignment problem, knapsack problem, orienteering, traveling salesman and vehicle routing problems, and maybe others.Among the methods we will learn: combinatorial algorithms, modelling and solving network problems as linear programs, simplex, dynamic programming, and (for the harder problems), branch-and-bound. For some of the hard problems, we will also discuss construction and improvement heuristics.This course is broad rather than deep, which means that we emphasise covering a good number of problems and methods, without spending too much time in any of them. The focus is on learning methods, and developing intuition behind why they work.
Assessment and permitted materials
2 exams, each corresponding to 40% of the final grade.
Several homeworks to be announced every week, and handed in in the beginning of the following class. These account for the remaining 20% of the grade.
Several homeworks to be announced every week, and handed in in the beginning of the following class. These account for the remaining 20% of the grade.
Minimum requirements and assessment criteria
Students should be familiar with Excel (in special, the Solver), and have basic knowledge about linear programming (i.e., understand a LP formulation, and how to apply the simplex method).This course requires a somewhat higher level of abstraction, when compared to a Bachelor course. Students are expected to spend around 1-2 hours per week in out-of-class studies (reviewing the content, and preparing the homeworks).
Examination topics
Reading list
Slides will be available through Moodle, and are sufficient for covering all the content of the course.For a quick review of linear programming, including the simplex method, students are referred to:Hillier, Lieberman. Introduction to Operations Research. Chapters 1-5.(Optional!) For a deeper and more rigorous understanding of many of the methods we see in this course, students are referred to:Bertsimas, D., Tsitsiklis, J. Introduction to Linear Optimization.
Association in the course directory
Last modified: Mo 07.09.2020 15:19