An Investigation of Hyper-Heuristic Approaches for Teeth Scheduling

Modern day production sites for teeth manufacturing often utilize a high-level of automation and sophisticated machinery. Finding efficient machine schedules in such a production environment is a challenging task, as complex constraints need to be fulfilled and multiple cost objectives should be minimized. This paper investigates a hyper-heuristic solution approach for the artificial teeth scheduling problem which originates from real-life production sites of the teeth manufacturing industry. We propose a collection of innovative low-level heuristic strategies which can be utilized by state-of-the-art selection-based hyper-heuristic strategies to efficiently solve practical problem instances. Furthermore, the paper introduces eight novel large-scale scheduling scenarios from the industry, which are included in the experimental evaluation of the proposed techniques. An extensive set of experiments with well-known hyper-heuristics on benchmark instances shows that our methods improve state-of-the-art results for the large majority of the instances.