Theses
Here you can find advertised final thesis topics, which are divided into research fields. Guidelines and helpful hints for the preparation of writing theses and other scientific work can be found under Downloads and Links. All mentioned topics can be edited in consultation with the supervisors and with a correspondingly adapted scope as a project, bachelor or master thesis.
In addition, you as a student have the opportunity to approach us at any time with your own ideas or suggestions for questions from the subject areas listed below and to work with us on a suitable topic for your project or thesis.
Topics
Optimization Problems in Logistics
Optimization methods are applied to numerous logistics issues. Due to the structure of logistic questions, the representation in mathematical models is suitable. The complexity of such problems leads to numerous interesting topics, such as the investigation of modelling approaches and solution methods in the fields of route planning, location planning or delivery network design.
Optimization methods are applied to numerous logistics issues. Due to the structure of logistic questions, the representation in mathematical models is suitable. The complexity of such problems leads to numerous interesting topics, such as the investigation of modelling approaches and solution methods in the fields of route planning, location planning or delivery network design.
Quantitative Modelling of Innovative Logistics Concepts
In both practice and research, there is a growing effort to develop innovative transport solutions that combine traditional trucks with drones or autonomous delivery vehicles to address the challenges of last-mile or inter-location logistics. The aim is to effectively combine the respective strengths of different delivery methods. For example, in 2023 REWE Group launched the "Liefer Michel" experiment, which combined drones and cargo bikes to deliver groceries to more remote areas (see https://www.rewe-group.com/de/presse-und-medien/newsroom/pressemitteilungen/in-michelstadt-der-bringer/). Merck tested the use of drones to transport medical samples between two nearby sites (https://www.merckgroup.com/de/research/science-space/envisioning-tomorrow/smarter-connected-world/wingcopter-hot-topic.html). The innovative combination of different modes of transport makes it possible to reduce traffic-related obstacles such as congestion or to bypass natural barriers by including airspace in the delivery process. These combinations contribute to greater flexibility and automation in the logistics process, which is particularly important for last-mile transport. Work in this area aims to develop appropriate quantitative models that allow the efficient integration and coordination of these different transport modes to optimise delivery processes.
Would you like to work on a question from this subject area in your project or final thesis? If you are interested, please approach:
Tobias Klein, Tizian Schug, Kai Hoth
Efficient Solution Methods for Mixed Integer Optimization Problems in Logistics
Many practical problems can be represented by mixed integer linear models, since some variables in reality can only assume integer values, e.g. number of packets to be sent, number of machines to be used, etc. In contrast to linear optimization, the solvability of mixed integer problems is made more difficult by the additional limitation of the decision variables. Exact methods, such as the branch-and-bound method, usually require too much computation to solve problems with a large number of integer variables and/or constraints. For this reason, heuristics are often used to provide a good (but not necessarily optimal) solution within a reasonable time. The aim of the work is to identify the advantages and disadvantages of heuristic and exact solution methods and to implement suitable solution methods for a selected problem in Python or MATLAB. (Note: Basic knowledge of programming is helpful)
Would you like to work on a question from this subject area in your project or final thesis? If you are interested, please approach:
Tobias Klein
Humanitarian Logistics
Humanitarian logistics is a broad field that involves the coordination and execution of operations aimed at saving and preserving lives in crisis situations. It encompasses the efficient planning and distribution of relief supplies, the formulation of evacuation strategies to ensure the safety of affected individuals, and the implementation of search and rescue operations. The following topics are available in this area:
Humanitarian logistics is a broad field that involves the coordination and execution of operations aimed at saving and preserving lives in crisis situations. It encompasses the efficient planning and distribution of relief supplies, the formulation of evacuation strategies to ensure the safety of affected individuals, and the implementation of search and rescue operations. The following topics are available in this area:
Optimization in Search-and-Rescue (SAR) Operations
In the aftermath of natural disasters and other emergency situations, finding missing people quickly and efficiently is often critical to their survival. Search and Rescue (SAR) operations face the challenge of operating under significant time pressure, often in difficult to access terrain. The integration of drones into SAR missions offers promising opportunities to cover search areas more quickly and effectively. To use this combination efficiently and purposefully, optimization models are needed that can coordinate SAR operations and maximize success rates based on often uncertain data. Key questions include: What uncertainties have the greatest impact on the coordination of SAR operations? What are the options for combining humans and drones in SAR operations, and how can they be modeled? What approaches are appropriate for real-world scenarios? Research in this area will focus on addressing these questions, as well as analyzing and possibly further developing quantitative models that have been proposed in the literature for search and rescue problems.
Would you like to work on a question from this subject area in your project or final thesis? If you are interested, please approach:
Tobias Klein
Would you like to work on a question from this subject area in your project or final thesis? If you are interested, please approach:
Kai Hoth, Tizian Schug
Would you like to work on a question from this subject area in your project or final thesis? If you are interested, please approach:
Kai Hoth
Would you like to work on a question from this subject area in your project or final thesis? If you are interested, please approach:
Recep Günes
Would you like to work on a question from this subject area in your project or final thesis? If you are interested, please approach:
Recep Günes
Would you like to work on a question from this subject area in your project or final thesis? If you are interested, please approach:
Tobias Klein
Energy technology and energy management
Energy is of central importance for almost all areas of life. Due to the indispensability of energy production on the one hand and its ecological impact on the other, it is a subject area of great social relevance. Energy generation from various sources and processes, energy distribution and storage as well as energy use by private and commercial end users offer many opportunities to improve efficiency. Optimizations are based on the target triangle between security of supply, economic efficiency and ecological sustainability.
Energy is of central importance for almost all areas of life. Due to the indispensability of energy production on the one hand and its ecological impact on the other, it is a subject area of great social relevance. Energy generation from various sources and processes, energy distribution and storage as well as energy use by private and commercial end users offer many opportunities to improve efficiency. Optimizations are based on the target triangle between security of supply, economic efficiency and ecological sustainability.
Optimization in energy technology and energy management
In many industrial sectors, energy consumption represents a significant cost factor and is therefore the subject of possible optimization measures. The redesign of technical processes or adjustments to product portfolios or production programs, for example, offer approaches for energy optimization. Due to the nature of energy as a supporting resource, various technical and economic constraints as well as different objectives must be taken into account. In the energy industry, issues arise in particular in the context of the energy transition that suggest the application of optimization models and methods. Sector coupling is based on the networking of a large number of players with different functions and individual objectives. The increasing decentralization in generation due to many small generation plants and the volatility of renewable energies ensure a high level of complexity. Energy grids are designed with the objectives of security of supply, economic efficiency and environmental sustainability in mind. The conflicting relationship between these objectives requires the determination of appropriate compromise-based solutions. Final theses can focus on optimizing the operation of smart grids or individual systems and pursue the goal of minimizing costs or emissions. In addition to the implementation of such a model, a component of such a thesis is the evaluation and analysis of the results of an exemplary case study. The specific topic is developed in consultation with the supervisor.
Would you like to work on a question from this subject area in your project or final thesis? If you are interested, please approach:
Kai Hoth, Tizian Schug
Mobility Services
In recent years, new Mobility Sservices have emerged that increasingly use Operations Research techniques to design processes more efficiently. New Mobility Services include bike sharing (such as StadtRAD, nextbike, JUMP and Mobike), car sharing (such as ShareNow and Oply), ride sharing (such as Uber, BlaBlaCar, MOIA and ioki) and E-Scooter sharing (such as Lime, Bird, TIER, Circ, Voi).
In recent years, new Mobility Sservices have emerged that increasingly use Operations Research techniques to design processes more efficiently. New Mobility Services include bike sharing (such as StadtRAD, nextbike, JUMP and Mobike), car sharing (such as ShareNow and Oply), ride sharing (such as Uber, BlaBlaCar, MOIA and ioki) and E-Scooter sharing (such as Lime, Bird, TIER, Circ, Voi).
Optimization of Innovative Mobility Services
For each type of new Mobility Service, there are different questions that can be answered with the help of optimization methods.
In the case of stationary or free-floating bike sharing, the routes of the service transporters for replacing and repairing the bicycles or the question of optimal new locations for bicycle stations are topics that can be mathematically optimized.
Car sharing offers similar research topics to bike sharing. An additional question is, for example, the optimization of the refueling (with fuel or electricity) of the vehicles in terms of time and/or location.
Ridesharing, which includes ridehailing (taxi rides), carpooling (commuter communities) and ridepooling (collective taxi rides), can benefit in different ways from methods of Operations Research. For example, vehicle routing and matching between vehicles and customers can be optimized, or dynamic pricing can be used to maximize revenue. On the Uber Engineering Blog you can find some articles and papers on the topic, e.g. "Dynamic Pricing and Matching in Ride-Hailing Platforms".
The probably most recent mobility service in Germany is E-Scooter sharing. E-Scooters are electrically driven scooters. Scientific literature on the optimization of this mobility service is still scarce. A research object is, for example, the optimization of evening rides, which are necessary to collect the scooters and charge them over night. E-Scooter sharing providers include myTaxi with the brand Hive, Bird, Lime or Tier Mobility.
The implementation of mathematical models, which is usually part of every thesis, and/or the analysis and evaluation of data can be done in GUSEK or Python.
The concrete topic is to be developed in consultation with the supervisor.
In the case of stationary or free-floating bike sharing, the routes of the service transporters for replacing and repairing the bicycles or the question of optimal new locations for bicycle stations are topics that can be mathematically optimized.
Car sharing offers similar research topics to bike sharing. An additional question is, for example, the optimization of the refueling (with fuel or electricity) of the vehicles in terms of time and/or location.
Ridesharing, which includes ridehailing (taxi rides), carpooling (commuter communities) and ridepooling (collective taxi rides), can benefit in different ways from methods of Operations Research. For example, vehicle routing and matching between vehicles and customers can be optimized, or dynamic pricing can be used to maximize revenue. On the Uber Engineering Blog you can find some articles and papers on the topic, e.g. "Dynamic Pricing and Matching in Ride-Hailing Platforms".
The probably most recent mobility service in Germany is E-Scooter sharing. E-Scooters are electrically driven scooters. Scientific literature on the optimization of this mobility service is still scarce. A research object is, for example, the optimization of evening rides, which are necessary to collect the scooters and charge them over night. E-Scooter sharing providers include myTaxi with the brand Hive, Bird, Lime or Tier Mobility.
The implementation of mathematical models, which is usually part of every thesis, and/or the analysis and evaluation of data can be done in GUSEK or Python.
The concrete topic is to be developed in consultation with the supervisor.
Would you like to work on a question from this subject area in your project or final thesis? If you are interested, please approach:
Kai Hoth
Optimization of Berth Allocation at Container Terminals
Container terminals (CTs) are the interface between sea-bound and hinterland transportation. However, the quay space is a critical resource on CTs as its capacity is limited by the quay’s length and the terminals working hours. Therefore, in order to use the quay optimally, terminal operators assign the berths to specific container vessels beforehand. The corresponding planning problem is called the Berth Allocation Problem (BAP). The aim of the BAP is to decide when and where to berth an incoming vessel and whether a vessel has to be rejected due to low quay capacity. Depending on the perspective, the objective may be maximizing the CTs returns or, e.g., maximizing the service level and the customer satisfaction respectively.
Container terminals (CTs) are the interface between sea-bound and hinterland transportation. However, the quay space is a critical resource on CTs as its capacity is limited by the quay’s length and the terminals working hours. Therefore, in order to use the quay optimally, terminal operators assign the berths to specific container vessels beforehand. The corresponding planning problem is called the Berth Allocation Problem (BAP). The aim of the BAP is to decide when and where to berth an incoming vessel and whether a vessel has to be rejected due to low quay capacity. Depending on the perspective, the objective may be maximizing the CTs returns or, e.g., maximizing the service level and the customer satisfaction respectively.
Cluster identification in model formulation for the BAP
Operations Research is focused on the formulation of mathematical models to simplify real-world planning problems and on the use of algorithms for solving these models. For more than 20 years research has been conducted on the BAP and a variety of model formulations were developed and improved. For a better understanding of the underlying concepts, model clusters are to be identified for the different model formulations within the relevant literature.
The main goal of your thesis will be the identification of basic mathematical models representing the model formulations from the relevant literature. Therefore, you will (1) provide an overview of the relevant literature, (2) group similar models based on their model formulation and (3) present the general, basic model formulation of each group. Moreover, you can apply the basic models of each cluster on a case study and analyze, e.g., the necessary computational effort and the objective function values.
Your results will feed into our research on the optimization of berth allocation scheduling at container terminals. The implementation of mathematical models, which is usually part of every thesis, and/or the analysis and evaluation of data can be carried out in Python.
The main goal of your thesis will be the identification of basic mathematical models representing the model formulations from the relevant literature. Therefore, you will (1) provide an overview of the relevant literature, (2) group similar models based on their model formulation and (3) present the general, basic model formulation of each group. Moreover, you can apply the basic models of each cluster on a case study and analyze, e.g., the necessary computational effort and the objective function values.
Your results will feed into our research on the optimization of berth allocation scheduling at container terminals. The implementation of mathematical models, which is usually part of every thesis, and/or the analysis and evaluation of data can be carried out in Python.
Would you like to work on a question from this subject area in your project or final thesis? If you are interested, please approach:
Recep Günes
Disruption Management in Berth Allocation Scheduling
As BAP is a real-world problem, where information may be incomplete or incorrect, the actual vessel arrival time and the handling time are uncertain or unknown when the vessel’s berth is to be scheduled. Reactive approaches, e.g. disruption management, aim at maintaining the berthing schedule’s feasibility, when newly gathered information differs from the (original) expectations, i.e. a disruption occurs.
The main goal of your thesis will be the application and analysis of a reactive optimization model for the BAP. Furthermore, the basics of the BAP and current literature on the BAP under uncertainty are to be presented and discussed.
Your results will feed into our research on the optimization of berth allocation scheduling at container terminals. The implementation of mathematical models, which is usually part of every thesis, and/or the analysis and evaluation of data can be carried out in Python.
The main goal of your thesis will be the application and analysis of a reactive optimization model for the BAP. Furthermore, the basics of the BAP and current literature on the BAP under uncertainty are to be presented and discussed.
Your results will feed into our research on the optimization of berth allocation scheduling at container terminals. The implementation of mathematical models, which is usually part of every thesis, and/or the analysis and evaluation of data can be carried out in Python.
Would you like to work on a question from this subject area in your project or final thesis? If you are interested, please approach:
Recep Günes