Bachelor and Master thesis

Here, you find specific topics tendered by the chair at the moment. If you are interested, please use the “Apply now” button above.

Bachelor theses

Currently, there are no tendered bachelor theses available. Please use the “Apply now” button and suggest your own topic.

Master theses

Topic: From disposable cardboard boxes as transport packaging to the circular packaging concept in B2B

Transport packaging in the B2B sector is currently characterized by single-use packaging cardboard boxes are standard in the packaging industry. As a manufacturer of flexible packaging made of plastic and paper, we currently deliver our bags packed in cardboard boxes on pallets without exception. Large stocks of cardboard packaging must be kept in stock with the corresponding capital commitment, storage space is required and the intensity of use is limited. As an owner-managed family business with a 50-year tradition that values sustainable and value-creating production methods, we see potential for improvement in optimizing transport packaging. The aim of the master’s thesis is to develop an approach for a packaging system that can be scaled to the entire logistics handling as a circular model.

For a more detailed description, please follow this link: PDF: From disposable cardboard boxes as transport packaging to the circular packaging concept in B2B

To this belongs:

• Data evaluation of current consumption and logistics movements
• Research on already existing reusable systems in the market that offer connection possibilities
• Development of own ideas for the implementation of a closed loop system in
  the company
• Qualitative and quantitative evaluation of possible returnable systems for use at Gruber
• Development of a possible strategy and implementation plan

Topic: Markdown optimization for fresh categories (Kaufland)

For a retailer, ordering the right quantity of products is a crucial task on a daily level – too much quantity leads to food waste whereas too little leads to out–of–stock situations, lost sales, and dissatisfied customers. Excess stocks are particularly critical in fresh categories since the items must be sold off within a very short time due to their short best–before date. In order to sell the items before they perish (e.g., before reaching the best before date), targeted discounts are given by the employees in the stores. If a price discount is too high, the remaining stock may be salvaged quickly, and the margin losses may be too high. On the other side, if the price discounts are too low, the risk of food waste increases.

The aim of this master’s thesis is to develop an approach for profit–optimized markdown pricing in fresh categories (bakery, dairy and/ or counter) on a market–specific and item–specific level, with the goal to minimize the total write–offs and waste (losses from price reduction and remaining stock).

For a more detailed description, please follow this link: PDF: Markdown optimization for fresh categories

The tasks include:

• Complete a structured literature review about markdown policies for overstocks
• Structurally derive decision problem and formalize it as a stochastic–dynamic optimization model
• Implement the decision problem as a simulation model (e.g., in Python or AnyLogic)
• Collect data from Kaufland and prepare it for the application
• Complete numerical studies to generate some managerial insights
• Develop plan for potential implementation of the tool at Kaufland

A real–world dataset will be provided

Topic: Predicting Holiday Effects on Retail Sales

For a retailer, ordering the right amount of product is a crucial task on the daily level – too much leads to spoilage/food waste, whereas too little leads to out-of-stock situations, lost sales, and dissatisfied customers. In particular, the days around holidays are of special interest and, at the same time, hard to forecast. The goal of this master’s thesis is to find underlying patterns in customer shopping behavior that help to predict the holiday week’s distribution – even for stores/articles that have never seen this holiday. For this task, a real-world dataset will be provided. On this basis, an exploratory analysis should be performed to identify relevant features to explain differences in holidays and derive probabilities for each day’s share of the week.

For a more detailed description, please follow this link: PDF: Predicting Holiday Effects on Retail Sales.

The specific tasks to be performed include:

• Exhaustive literature review concerning the state-of-the-art concerning the prediction of holiday effects on retail sales
• Data preparation/cleaning of non-holiday effects (second holiday/paycheck day with increased sales within the week, seasonality, external shocks (e.g., Corona pandemic))
• Exploring possibilities to derive holiday week distributions from the data

Topic: Food waste in the hospitality and food service sector

Catering for a large number of people, as is the case in canteens, at events, or in hotels, for example, poses major challenges for service providers. Consumers require an attractive offer of dishes, while their preferences and hunger are hardly known. At the same time, the provider must prevent empty buffets and sold-out meals at all costs, a setting that practically provokes food waste. We want to approach this problem from the providers’ point of view, analyze the current way of planning the quantities and meals in facilities such as hotels, canteens, mass catering, etc. and find strategies for improvement.

The Master thesis should cover the following tasks:

• Literature overview of planning approaches in this area (both empirical and modeling-based)
• Development of an interview guide based on open research questions appearing from the literature review (in coordination with the supervisor)
• Finding and contacting suitable interviewees
• Conducting the interviews and analysis of the gathered information via qualitative content analysis
• Derivation of improvement measures

Topic: Network Planning with micro-fulfillment centers

Quick-commerce players such as Gorillas or Flink are expanding massively in Europe. In order to achieve this short lead time, they promise their customers building micro-fulfillment centers in urban areas can be a solution. We want to apply operations research methods to analyze how to improve their distribution network, especially where to locate the MFCs.

For your master thesis, you will have the following tasks:

• Perform research and literature review on location routing problems
• Implement a mathematical decision model in Python or CPLEX, or GAMS (your choice)
• Analyze findings in paper
• Determine business implications and potential research areas based on the findings

Topic: The Electric Vehicle Routing Problem

The European Union requires all new vehicles to be zero-emission by 2035 (European Commission, 2021). This leads to a significant change in the mobility sector. At the current point in time, electric cars cannot travel as far and cannot refuel as fast as their combustion engine counterparts.

The Electric Vehicle Routing Problem (E-VRP) extends the classical Vehicle Routing Problem (VRP) with a limited driving range and the necessity of charging a vehicle. The E-VRP for this thesis considers a linear charging function and time windows. The VRP is a generalization of the well-known Travelling Salesman Problem (TSP) to multiple vehicles.

The tasks for students are to:

• Give an overview of the literature on Electric Vehicle Routing Problems
• Implement the mathematical model (E-VRP) of Schneider et al. (2014) in Python and solve it with a commercial solver (Gurobi)
• Implement a column generation algorithm in Python and evaluate its performance against the commercial solver (Gurobi)
• Investigate the effect of varying battery sizes and charging speeds in a computational study

Literature: Schneider, M., Stenger, A., & Goeke, D. (2014). The electric vehicle routing problem with time windows and recharging stations. Transportation Science, 48(4), 500-520.

Topic: The Stochastic Patient-to-Bed Assignment Problem

Patients who are admitted to a hospital as inpatients must be assigned a bed while respecting certain constraints. For instance, gender-mixed rooms are usually to be avoided, and it is desirable to assign patients of similar age to a room since this has been shown to increase patient satisfaction. Transfers of a patient to a different room during their stay are possible but should be minimized in order to reduce work for the nurses and stress for the patients. The goal of the master’s thesis is to go beyond a rolling horizon approach by formulating the patient-to-bed assignment problem with stochastic arrivals and lengths of stay of patients using Markov decision processes (MDPs).

For a more detailed description, please follow this link: PDF: The Stochastic Patient-to-Bed Assignment Problem

The specific tasks to be performed include:

• Generate explicit distributions and test instances from the real data set
• Set up an automated instance generator
• Formulate an MDP for the case with a stochastic length of stay
• Formulate an MDP for the case where both length of stay and patient arrivals are stochastic