Master Thesis Opportunity in Logistics and Technology

2 weeks ago


Gothenburg, Västra Götaland, Sweden Ongoing Full time
About the Company

Ongoing is a leading software company specializing in logistics-intensive solutions. Our service enables millions of consumers and businesses to receive their products with a seamless customer experience. We've developed our software over many years through close collaboration with customers and partners, striving to simplify and connect the complex world of logistics. As the market leader in our niche in the Nordic countries, we've built the largest software ecosystem in the market.

Our office is conveniently located just outside the Chalmers Johanneberg campus, making it easy to attend meetings with our supervisor and other events.

Qualifications

We're looking for students with knowledge and interest in IT and programming. It's great if you also enjoy interacting with customers and finding business interesting. Most importantly, you should be excited to work with an entrepreneurial-driven software company where curiosity, responsibility, and flexibility are key to future success. At least professional working proficiency in a Scandinavian language and English is required.

Our employees come from various engineering backgrounds, and almost all have a master's degree in Technology. The company's aim is to hire full-time employees after the thesis project.

Subject

There are numerous opportunities to write a thesis at the intersection of Technology and Logistics. Previous theses have focused on large-scale optimization, eCommerce picking, and software testing. If you have specific subjects in mind, we're happy to help you find mutual interests. Our engineers may also have ideas you can explore. Here are some potential pitches:

Suggesting Packaging with Machine Learning

One of the significant challenges in eCommerce is the inefficient use of packaging materials, leading to high resource consumption and environmental impact. By applying machine learning, we can suggest optimized packaging solutions based on product information. This could involve using genetic algorithms to find the most efficient packaging configurations.

Using Artificial Intelligence for Warehouse Location Optimization

The picking process in warehouses is often time-consuming, with most time spent moving between locations. We can explore AI techniques to improve picking efficiency, such as association rule learning. This could help our customers optimize their warehouse layouts and reduce costs.

Order Batching Problem

Batch picking is a common strategy in eCommerce, where pickers collect products for multiple orders in a single pass. However, this approach can lead to challenges in distributing individual orders into optimal batches. We can use large-scale optimization methods, such as Dantzig-Wolfe decomposition, to improve batching efficiency.

Previous Work

Ongoing has a successful history of offering Master Thesis projects, with many leading to employment after completion. While not all theses are published, we've listed some examples of published work:

  • Walk less, pick more: choosing optimal batches of orders in a warehouse
  • Enhancing Association Rule Mining for Solving the Storage Location Assignment Problem
  • Batch Picking in Warehouse Logistics: Trading Optimality for Feasibility
  • Optimizing Box Sizes for Shipping in E-Commerce - A Mixed-Integer Linear Programming and a Genetic Algorithm Approach
Formalities

As a thesis student at Ongoing, you'll be guided by a supervisor who recently completed their own thesis. We provide computer and office space in our Johanneberg, Gothenburg office, as well as complementary fruit, coffee/tea, and lunch (three times a week). The office is located on Chalmers' campus, making it easy to attend meetings with your supervisor and other events. As compensation, 30,000 SEK is paid out to each student when the University has approved the thesis.



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