Research Areas

Prof. Dr. Thomas Weise (汤卫思) contributes research to a variety of areas of optimization, operations research, and metaheuristics. Here you can find an overview of several of them.

Frequency Fitness Assignment

Frequency Fitness Assignment&nbsp(FFA, 频率适应度分配) is a novel approach to metaheuristic optimization. Actually, it abandons the very core principles of metaheuristic optimization. And yet, it works.

In the field of optimization, benchmarking is the research area focussed on how to investigate algorithm performance experimentally. The goal is to get a reliable and replicable impression of how good and how efficient algorithms are. This then serves as foundation for the decision which algorithm to use for a given real-world problem and/or how we may improve performance by research. Since this research direction is a mixture of experiments and statistics, it gives me a chance to do some programming for research (yeah!) and contribute packages like moptipy which practically implement theoretically-grounded best practices into industry-grade software based on many years of experience.

Traveling Salesperson Problem

The Traveling Salesperson Problem (TSP) is one of the most important combinatorial optimization tasks, one of the classical tasks from the field of Operations Research. Here, the goal is to find the shortest round-trip tour through n cities and back to the origin. A TSP instance is defined by the number of cities and their distances. In a symmetric instance, the distance from A to B is the same as the distance from B to A, in an asymmetric instance, this is not necessarily true.

Logistics

Logistics is a huge area that poses a wide range of different optimization problems. It comprises many sub-fields, ranging from classical tasks like the TSP to more general problems that are very constraint and specific to a particular company. I have contributed to many of these fields.

Packing and Cutting Problems

Packing is a research field very closely related to logistics. Here, the goal is to pack objects of certain sizes into containers of given sizes. The objects may be one-, two-, or three-dimensional. It may or may not be permitted to rotate them when packing them. Often, the goal is to use as few containers as possible.

Genetic Programming

Genetic Programming (GP) means to perform evolutionary search in a tree-based search space. Often, such trees are designed to represent programs of sorts, sometimes classifiers. This field is somehow in decline with the advent of deep learning. However, there are quite a few interesting things that can be done.

Distributed Systems

Distributed systems comprise a wide range of interacting components, such as computer networks, network applications, or multi-agent systems. Since I did my PhD at the Distributed Systems Group of the University of Kassel (德国卡塞尔大学), naturally, this is also one of my research interests.

Teaching

Teaching lies on the fringes of my research interests. One of the very first research-related works I did was actually the development of a what-you-see-is-what-you-get editor for teaching material. Even now, I am still creating my own systems for generating teaching material and used them two write books and slides for my own classes. The latest iteration of this never-ending struggle is using GitHub actions to build teaching material located in GitHub repositories and a LaTeX/Python package from including data from other repositories in such material. I used this material to write my books Programming with Python and Databases in 2025. Thus, I think teaching does qualify as a resarch direction for me, too.