A Survey of Hyper-heuristics for Dynamic Optimization Problems

Dynamic optimization problems have attracted the attention of researchers due to their wide variety of challenges and their suitability for real-world problems. The application of hyper-heuristics to solve optimization problems is another area that has gained interest recently. These algorithms can apply a search space exploration method at different stages of the execution for finding high quality solutions. However, most of the proposed works using these methodologies do not focus on the development of hyper-heuristics for dynamic optimization problems. Despite that, they arise as very appropriate methods for dynamic problems, being highly responsive and able to quickly adapt to any possible changes in the problem environment. In this paper, we present a brief study of the most salient previously proposed hyper-heuristics to solve dynamic optimization problems, and classify them, taking into consideration the complexity of their low-level heuristics. Then, we identify some the most important research areas that have been vaguely explored in the Literature yet.