Announcement of new topics
Please note that topics are posted on a continuous basis.
Current Theses (partially in German)
Solving container relocation problems at intermodal container terminals
2024/05/16
Bachelor thesis
Due to the growing global container trade, efficient handling of containers is essential. To optimize the performance of terminals, efficient container relocation (reshuffle) is crucial, especially in intermodal terminals where container relocation plays an important role. Therefore, this work aims to employ the beam search method (or branch-and-bound method) to achieve the minimum number of container relocations.
Interested in this topic? Please use the application form on our website!
Supervisor: Setareh Behzadi, M.Sc.
Container relocation problem: application of a reinforcement learning approach
2024/05/16
Bachelor thesis, Master thesis
Efficient container relocation, or reshuffling, is important for terminal yard management, especially with the increasing global volume of containerized trade. To solve the container relocation problem in intermodal terminals, this work focuses on a simple yard structure and aims to investigate the application of reinforcement learning, especially the Q-learning method. The results, such as the relocation rate, will be assessed using a heuristic approach.
* Previous knowledge of Python and reinforcement learning methods is mandatory.
Interested in this topic? Please use the application form on our website!
Supervisor: Setareh Behzadi, M.Sc.
Optimizing container operations at multimodal terminals: A literature review of machine/reinforcement learning methods
2024/05/16
Bachelor thesis
The growing global container trade requires efficient handling and transportation of terminal containers to optimize the performance of inland container terminals and ports. As the demand for fast, efficient transshipment of terminal containers increases, innovative approaches are needed to improve measures such as task completion time, energy consumption, and overall operational efficiency. In multimodal terminals, the cranes generally serve the container ships, trucks, rail, and stacking areas. Unproductive movements of the cranes, for example in container relocation (reshuffling), should be minimized to improve the efficiency of the terminal. Intelligent methods such as machine/reinforcement learning can provide potential solutions. Therefore, this work aims to review the existing literature and develop innovative solutions for managing container relocation.
Interested in this topic? Please use the application form on our website!
Supervisor: Setareh Behzadi, M.Sc.
Benders Decomposition for robotized delivery on the last mile
2023/05/24
Master thesis
The aim of the thesis is to understand the concept of Benders Decomposition and to apply it to the delivery of customer goods on the last mile, making use of the concept “vans and robots”. Hereby, the work of Alfandari et al. (2022) sould be understood and slightly extended.
Literature: Alfandari, L.; Ljubić, I.; da Silva, M.D.M. (2022): A tailored Benders decomposition approach for last-mile delivery with autonomous robots. European Journal of Operational Research, 299(2), 510-525.
Interested in this topic? Please use the application form on our website!
Supervisor: Prof. Dr. Felix Weidinger
The Branch-and-Bound procedure for the classical Traveling Salesman Problem: Building a Demonstrator as an Open Educational Resource
2023/05/24
Bachelor thesis
The Traveling Salesman Problem (TSP) as well as the Branch-and-Bound procedure (B&B) are both classics in Operations Research, tackled in many courses at different universities. The goal of this thesis is to develop a demonstrator which applies B&B to the TSP, using some simple bounds and branching schemes. The algorithm, hereby, needs to be visualized in a suitable manner, such that it can be used for educational purposes. The goal is to provide the demonstrator as an Open Educational Resource, ultimately, such that the outcome of the thesis can be used freely in any Operations Research course.
Interested in this topic? Please use the application form on our website!
Supervisor: Prof. Dr. Felix Weidinger
Development and benchmarking of a heuristic solution method for the picker routing problem in mixed shelves storage warehouses
2023/05/10
Bachelor thesis, Master thesis
The steady growth of the e-commerce industry, especially fuled by the pandemic, puts increased pressure on various warehouse operations. One potential approach to increase order picking efficiency is to reduce picker walking distances. The unique feature in mixed shelves storage warehouses is that items to be picked can be located in multiple storage positions in the warehouse. This results in a multi-layered optimization problem: Suitable positions must be selected as well as the shortest route between them has to be found. The goal of this thesis is to develop a heuristic solution for the picker routing problem in mixed shelves storage warehouses, to implement it and to test it against existing methods.
Interested in this topic? Please use the application form on our website!
Supervisor: Constantin Wildt, M.Sc.
Optimization of randomized control rules for cleaning robots
2022/03/29
Bachelor thesis
Decentralised acting cleaning robots usually operate on a static rule set. The aim of this work is to simulate different rule sets in different environments and to identify reasonable rules. Knowledge of implementation or the willingness to learn is a requirement for this.
Interested in this topic? Please use the application form on our website!
Supervisor: Prof. Dr. Felix Weidinger