关键词: 超启发算法, 选择式, 生成式

Abstract: Hyper-heuristics algorithms seek to efficiently solve the combinatorial optimization problems. It is expected to handle classes of problems rather than solving just one problem. This paper presents a systematic review of the research progress of hyper-heuristic algorithms. Based on a brief introduction to hyper-heuristic definition, structure and classification, the heuristic selection and heuristic generation approaches of hyper-heuristics are summarized. The techniques such as the machine learning methods in choosing low-level heuristics, the move acceptance criterions for neighborhood solutions, the generation of low-level heuristics, and the algorithm framework are discussed in details. Finally, the limitations and further research directions of hyper-heuristics algorithms are discussed.

Key words: hyper-heuristics algorithm, selection, generation