Master thesis

Motivation

The planning of transport capacities under demand fluctuations represents one of the central challenges in the transportation sector-both in freight and passenger transport. In passenger transport, factors such as demographic developments, mobility behavior, and technological innovations significantly influence demand, whereas in freight transport, economic conditions, structural change, and globalization are the primary sources of uncertainty (Asgarpour et al., 2023). The consequences of these uncertainties range from suboptimal capacity utilization and increased costs to supply bottlenecks or overcapacity. Consequently, methods from Operations Research (OR) are increasingly being applied in both sectors to enable robust and efficient planning decisions. However, the requirements, modeling approaches, and objectives often differ substantially between freight and passenger transport, for example with respect to the importance of time windows, flexibility, price sensitivity, or service quality. To date, a systematic comparison of the OR methods proposed in the literature for addressing demand uncertainty in both sectors has rarely been conducted.

Objective

The aim of this master’s thesis is to conduct a systematic literature review that examines and compares OR methods for transport planning under demand uncertainty in both freight and passenger transport. The focus lies on the identification and classification of modeling approaches used in the scientific literature-for instance, stochastic optimization, robust optimization, or hybrid methods. The respective strengths and weaknesses of these methods are to be analyzed in the context of both transport types, particularly with regard to the modeling of uncertainty, objective functions (e.g., costs, capacity utilization, service level), the consideration of overbooking strategies or flexibility options, and practical applicability. The goal is to identify commonalities and differences in methodological approaches as well as open research questions, and to derive recommendations for the application of specific OR methods in the two sectors.

Literature

• Asgarpour, S., Hartmann, A., Gkiotsalitis, K., & Neef, R. (2023). Scenario-Based Strategic Modeling of Road Transport Demand and Performance. Transportation Research Record, 2677(5), 1415-1440. https://doi.org/10.1177/03611981221143377
• Kitchenham, B., Charters, S. (2007): Guidelines for performing systematic literature reviews in software engineering. In: Keele University and Durham University Joint Report, EBSE-2007-01.
• Durach, Christian F.; Kembro, Joakim; Wieland, Andreas (2017): A New Paradigm for Systematic Literature Reviews in Supply Chain Management. Journal of Supply Chain Management 53(4), 67–85. https://doi.org/10.1111/jscm.12145

General Conditions

Basic knowledge of Operations Research is required, as the thesis necessitates a critical examination of mathematical models and optimization techniques.

If you are interested in writing this thesis, please send your transcript of records to Yuerui Tang. In a meeting, the modalities and focus of the work can be discussed. You can start your work asap.

Unternehmensführung und Logistik

Supervisor: Yuerui Tang, M.Sc.

Bachelor thesis

Produktion und Supply Chain Management

Supervisors: Dr. Ting Zheng, Prof. Dr. Christoph Glock

Announcement as PDF

Bachelor thesis

Produktion und Supply Chain Management

Supervisors: Dr. Ting Zheng, Prof. Dr. Christoph Glock

Announcement as PDF

Master thesis

Gründungsmanagement

Supervisors: Prof. Dr. Carolin Bock, Mukunthan Nadarajah, M.Sc.

Announcement as PDF

Master thesis

Gründungsmanagement

Supervisors: Prof. Dr. Carolin Bock, Mukunthan Nadarajah, M.Sc.

Announcement as PDF

Bachelor thesis

Overview

AI systems supporting human decision-making introduce significant cognitive challenges for users. Concepts such as cognitive load and mental models are critical for understanding how users interact with these systems, especially in fields like healthcare where decisions carry high stakes. Cognitive load affects a user’s ability to process explanations, while mental models shape how users perceive and trust AI systems. Understanding these cognitive components is essential for designing AI systems that effectively support decision-making.

This thesis will focus on conducting a systematic literature review to explore how cognitive load and mental models are integrated into AI-augmented decision-making systems. The review will categorize existing research, identify gaps, and provide recommendations for integrating cognitive theories into the design of uncertainty-aware explanations.

Application

Please email your CV, transcript, and a brief statement of interest to jaki@tu-… . Familiarity with literature review methods or cognitive psychology is a plus. Suggestions for related topics are also welcome.

Information Systems & E-Services

Supervisor: Paula Jaki, M.Sc.

Bachelor thesis, Master thesis

Overview

Expert perspectives play a crucial role in understanding the real-world applicability of AI systems, particularly when it comes to communicating uncertainty. This thesis will involve conducting semi-structured interviews with experts (e.g., medical professionals, data scientists, or policy advisors) to explore their views on the design and use of uncertainty-aware explanations in healthcare AI systems.

The goal is to analyze how experts perceive uncertainty communication, identify practical challenges, and uncover opportunities for integrating uncertainty-aware explanations into healthcare workflows. Findings will contribute to the development of user-centered, ethically aligned AI systems.

Application

To apply, send your CV, transcript, and a statement of interest to jaki@tu-… . Strong communication skills and an interest in qualitative research methods are required. Prior experience with interview-based studies is a plus.

Information Systems & E-Services

Supervisor: Paula Jaki, M.Sc.

Bachelor thesis, Master thesis

Overview

AI-augmented decision-making systems are increasingly adopted in high-stakes fields such as healthcare, where decisions often involve complex trade-offs and uncertainty. However, many AI systems fail to effectively communicate this uncertainty to users, which can negatively impact trust, reliance, and decision quality. Designing uncertainty-aware explanations that dynamically interact with users offers an opportunity to bridge this gap and support better decision-making.

This thesis aims to adopt a Design Science Research (DSR) approach to develop and evaluate an interactive prototype for uncertainty-aware explanations in AI systems. The prototype will focus on how explanations can adapt to user preferences, cognitive load, and decision stakes. The study will involve iterative artifact development and evaluation with real or simulated users in a healthcare decision-making context.

Application

Please send your CV, transcript, and a short motivational letter detailing your interest in the topic and prior experience with design or human-computer interaction research to jaki@tu-… . A strong interest in design methodologies and user experience research is essential. Programming skills (e.g., Python, Figma) and familiarity with human-AI interaction are advantageous.

Information Systems & E-Services

Supervisor: Paula Jaki, M.Sc.

Bachelor thesis, Master thesis

Overview

Simulation-based research provides an effective method for exploring human-AI interaction in controlled environments. When uncertainty-aware explanations are introduced into AI systems, their influence on trust, reliance, and decision quality can vary based on task complexity and user characteristics. Simulations offer a way to systematically test these relationships and generate insights for real-world applications.

This thesis will focus on developing a simulation framework to study the impact of uncertainty-aware explanations on user behavior in AI-augmented decision-making. The simulation will include scenarios with varying levels of uncertainty and decision stakes, allowing for empirical analysis of how these factors influence user outcomes.

Application

Please send your CV, transcript, and a brief motivational statement to jaki@tu-… . A strong interest in programming (e.g., Python, PyTorch, or simulation tools), experimental design, and data analysis is essential.

Information Systems & E-Services

Supervisor: Paula Jaki, M.Sc.

Bachelor thesis, Master thesis

Deepfakes refer to synthetic media content—especially videos, images, and audio recordings—manipulated using artificial intelligence to create highly realistic but fabricated representations. The technology is rapidly evolving and increasingly capable of producing convincing and easily accessible content. While deepfakes were initially used in entertainment, they are now emerging in politically and economically relevant contexts. This development presents new challenges for societies, governments, and private sector organizations.

The proliferation of deepfakes introduces several critical issues. For businesses, manipulated media can result in significant reputational damage, loss of trust, or financial harm. Deepfakes have already been used to impersonate executives, falsify internal communications, or manipulate markets. High-profile incidents, such as the deepfake attack on Bayer or similar occurrences in Hong Kong, highlight how such technologies are used with the intent to deceive and cause disruption. Despite growing attention, there is limited systematic research on real-world deepfake cases and their implications for organizations, particularly within the European context.

If you are interested in writing your thesis on this topic, please contact me (saha@ise.tu-…) via email for further information. Please include your CV and transcript of records with your request.

Information Systems & E-Services

Supervisor: Ria Saha, M. Sc.

Bachelor thesis, Master thesis

Algorithmic management – the use of advanced algorithms, such as machine learning, to automate coordination and control functions—holds significant potential for modernizing public bureaucracies. Facing increasing demographic pressures and the imperative of digital transformation, public-sector organizations in Germany are actively seeking solutions to streamline processes traditionally managed by human personnel.

This thesis addresses algorithmic management within the German public sector through two primary objectives: first, synthesizing existing academic literature to systematically identify prevalent use cases and practical applications; second, empirically exploring facilitators and barriers influencing the adoption and integration of algorithmic management technologies. Through qualitative interviews with public servants, this research aims to provide nuanced insights into organizational readiness, cultural acceptance, and structural constraints, thus contributing to both theoretical understanding and practical guidance for future implementations.

This thesis can be written in German or English. However, given the international relevance of the topic, we strongly recommend writing it in English. If you are interested, please contact Armin Alizadeh with a short curriculum vitae and current performance record.

Information Systems & E-Services

Supervisor: Armin Alizadeh, M. Sc.

Bachelor thesis

Management Science / Operations Research

Bachelor thesis

Management Science / Operations Research

Master thesis

Management Science / Operations Research

Bachelor thesis

Management Science / Operations Research

Master thesis

Overview

Agile methods, such as Scrum, have revolutionized software development, enabling faster delivery and higher quality products. Their success in small, co-located teams has driven organizations to adopt agile practices in large-scale settings, using frameworks such as SAFe and Scrum of Scrums. While a key objective of agile methods is reducing time to delivery—and agile teams are often evaluated on velocity—time-related aspects in agile ISD literature remain underexplored.

In scaled agile contexts, one critical temporal success factor is synchronization among agile development teams. However, we do not yet know how temporal synchronization occurs. What challenges hinder effective synchronization? Could factors like shared temporal cognition, temporal reflexivity, time consciousness, temporal coordination, or team polychronicity act as enablers for effective synchronization?

This thesis seeks to qualitatively and exploratively investigate the mechanisms and enablers of synchronization among agile software development teams operating in scaled-agile environments. The research methodology may involve qualitative interviews or one or more case studies.

Information Systems & E-Services

Supervisor: Dr. Lea Müller

Bachelor thesis, Master thesis, Studienarbeit, Master thesis (15 CP), Master thesis (30 CP)

Technologie- und Innovationsmanagement

Supervisor: Christian Tschiedel, M.Sc.

Master thesis, Master thesis (30 CP)

Problem: Hypothetical Bias refers to the phenomenon where individuals behave differently in hypothetical decision-making situations compared to real ones, where actual consequences are involved. This presents a challenge, as individual preferences collected in surveys or experiments may not reflect real-world decisions, leading to inaccurate predictions and potential misjudgments. Various methods have been developed to reduce this bias.

Objective: This master's thesis aims to combine an in-depth review of the relevant literature on Hypothetical Bias with the development of a method to minimize it in experimental and survey settings. In collaboration with the behavioral market research start-up Aybee, you will have the opportunity to implement and test the developed approaches. These methods will be validated through A/B testing to more accurately capture real-world decision-making processes.

This thesis is supervised in cooperation with Aybee GmbH.

Interested in this thesis? Please send your application including your CV, transcript of records and short letter to Léonie Lange.

Technologie- und Innovationsmanagement

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!

Management Science / Operations Research

Supervisor: Setareh Behzadi, M.Sc.

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!

Management Science / Operations Research

Supervisor: Setareh Behzadi, M.Sc.

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!

Management Science / Operations Research

Supervisor: Setareh Behzadi, M.Sc.

Master thesis

Wirtschaftsinformatik | Software & Digital Business

Supervisor: Anna Maria Schätzle, M.Sc.

Master thesis

Wirtschaftsinformatik | Software & Digital Business

Supervisor: Anna Maria Schätzle, M.Sc.

Master thesis

Wirtschaftsinformatik | Software & Digital Business

Supervisor: Anna Maria Schätzle, M.Sc.

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!

Management Science / Operations Research

Supervisor: Prof. Dr. Felix Weidinger

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!

Management Science / Operations Research

Supervisor: Prof. Dr. Felix Weidinger

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!

Management Science / Operations Research

Supervisor: Constantin Wildt, M.Sc.

Bachelor thesis, Master thesis

Wirtschaftsinformatik | Software & Digital Business

Announcement as PDF

Bachelor thesis, Master thesis

Wirtschaftsinformatik | Software & Digital Business

Announcement as PDF

Bachelor thesis, Master thesis

Wirtschaftsinformatik | Software & Digital Business

Announcement as PDF

Master thesis, Master thesis (30 CP)

Your task is to replicate the coding of an existing agent-based model using the platform Repast Simphony, or to code your model of choice using the platform Repast Simphony and analyse it. For the latter option, you may choose a textbook model you learned about during your studies, or a topic from another area of interest.

If you are interested please contact Michael Neugart via michael.neugart@tu-….

Finanzwissenschaft und Wirtschaftspolitik

Supervisor: Prof. Dr. Michael Neugart

Master thesis, Master thesis (30 CP)

Your task is to replicate an empirical research paper with the data used in the original publication and add further robustness analyses, or to replicate the research paper using similar data, e.g. from another country.

Guide for replication studies (opens in new tab)

If you are interested please contact Darius Griebenow via darius.griebenow@tu-… or Michael Neugart via michael.neugart@tu-…

Supervisor: Darius Griebenow (M. Sc.) or Prof. Dr. Michael Neugart

Finanzwissenschaft und Wirtschaftspolitik

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!

Management Science / Operations Research

Supervisor: Prof. Dr. Felix Weidinger

Bachelor thesis, Master thesis

Wirtschaftsinformatik | Software & Digital Business

Announcement as PDF

Bachelor thesis, Master thesis

Wirtschaftsinformatik | Software & Digital Business

Announcement as PDF

Bachelor thesis, Master thesis

Wirtschaftsinformatik | Software & Digital Business

Supervisor: Dr. Mariska Fecho

Announcement as PDF

Bachelor thesis, Master thesis

Wirtschaftsinformatik | Software & Digital Business

Announcement as PDF

Master thesis

Wirtschaftsinformatik | Software & Digital Business

Supervisors: Dr. Amina Wagner, Dr. Anne Zöll

Announcement as PDF

Bachelor thesis, Master thesis (15 CP)

Wirtschaftsinformatik | Software & Digital Business

Supervisor: Dr. Nihal Wahl

Master thesis

Bachelor thesis, Master thesis

Supervisor: Prof. Dr. Simon Emde

Bachelor thesis, Studienarbeit

Zivilrecht, Gewerblicher Rechtsschutz und Urheberrecht sowie Recht der Informationsgesellschaft

Supervisors: Dr. jur. Anna-Lena Fehr, geb. Wirz, RA Matthias Prinz

Bachelor thesis, Studienarbeit

Supervisors: Dr. jur. Anna-Lena Fehr, geb. Wirz, RA Matthias Prinz

Bachelor thesis, Master thesis, Studienarbeit

Supervisor: Dipl.-Phys. Tobias Bier

Bachelor thesis, Master thesis, Studienarbeit, Diploma thesis

Supervisor: Prof. Dr. Peter Buxmann

Announcement as PDF