arXiv:2606. 14202v1 Announce Type: cross Abstract: Large Language Models (LLMs) have advanced Automatic Heuristic Design (AHD) by enabling heuristic generation through reasoning and code synthesis.
By Zishang Qiu, Xinan Chen, Rong Qu, Ruibin Bai
arXiv:2606. 29082v1 Announce Type: cross Abstract: Would experience designing faster GPU kernels also help close in on a long-standing open mathematical conjecture?
By Young-Jun Lee, Seungone Kim, Minki Kang, Alistair Cheong Liang Chuen, Zerui Chen, Seungho Han, Taehee Jung, Dongyeop Kang
arXiv:2605. 08756v2 Announce Type: replace Abstract: Automatic heuristic design (AHD) has emerged as a promising paradigm for solving NP-hard combinatorial optimization problems (COPs).
By Haoze Lv, Ning Lu, Ziang Zhou, Yew-Soon Ong, Shengcai Liu
arXiv:2506. 02594v2 Announce Type: replace Abstract: Large language models (LLMs) are increasingly used to synthesize heuristic programs, yet most existing pipelines optimize solvers against fixed benchmark distributions.
By Ruibo Duan, Yuxin Liu, Haoran Ye, Xinyao Dong, Zhiqiang Xu, Chenglin Fan
arXiv:2607. 11916v1 Announce Type: cross Abstract: The integration of Large Language Models (LLMs) with evolutionary computation has emerged as a powerful paradigm for automated heuristic design in combinatorial optimization.
By Nam Do Khanh, Nhat Nguyen Tran Minh, Dat Pham Vu Tuan, Long Doan, Binh Huynh Thi Thanh
arXiv:2608. 03129v1 Announce Type: new Abstract: Large Language Model-assisted Evolutionary Search (LES) has emerged as a powerful paradigm for automated algorithm design.
By Qinglong Hu, Qingfu Zhang, Fei Liu, Xialiang Tong, Kun Mao, Mingxuan Yuan