An Investigation of Hyper-Heuristic Approaches for Teeth Scheduling

Abstract

Finding efficient machine schedules in the area of teeth manufacturing 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. We propose low-level heuristic strategies which can be utilized by state-of-the-art selection-based hyper-heuristic strategies to efficiently solve large problem instances. An extensive set of experiments on the benchmark instances shows that the proposed approach can improve results for several realistic scenarios.