Automated Metaheuristic Algorithm Design with Autoregressive Learning

arXiv:2405.03419v1 Announce Type: cross
Abstract: Automated design of metaheuristic algorithms offers an attractive avenue to reduce human effort and gain enhanced performance beyond human intuition. Current automated methods design algorithms within a fixed structure and operate from scratch. This poses a clear gap towards fully discovering potentials over the metaheuristic family and fertilizing from prior design experience. To bridge the gap, this paper proposes an autoregressive learning-based designer for automated design of metaheuristic algorithms. Our designer formulates metaheuristic algorithm design …

abstract algorithm algorithm design algorithms arxiv automated autoregressive beyond clear cs.lg cs.ne current design family gap human intuition performance reduce scratch type