4 papers
CoupleEvo: Evolving Heuristics for Coupled Optimization Problems Using Large Language Models
Thomas Bömer, Bastian Amberg, Max Disselnmeyer +1
Many real-world optimization problems consist of multiple tightly coupled subproblems whose solutions must be coordinated to achieve high overall performance. However, existing lar…
The Multi-AMR Buffer Storage, Retrieval, and Reshuffling Problem: Exact and Heuristic Approaches
Max Disselnmeyer, Thomas Bömer, Laura Dörr +2
Buffer zones are essential in production systems to decouple sequential processes. In dense floor storage environments, such as space-constrained brownfield facilities, manual oper…
Algorithmic Prompt-Augmentation for Efficient LLM-Based Heuristic Design for A* Search
Thomas Bömer, Nico Koltermann, Max Disselnmeyer +2
Heuristic functions are essential to the performance of tree search algorithms such as A*, where their accuracy and efficiency directly impact search outcomes. Traditionally, such…
Leveraging Large Language Models to Develop Heuristics for Emerging Optimization Problems
Thomas Bömer, Nico Koltermann, Max Disselnmeyer +2
Combinatorial optimization problems often rely on heuristic algorithms to generate efficient solutions. However, the manual design of heuristics is resource-intensive and constrain…