Learning from Offline and Online Experiences: A Hybrid Adaptive Operator Selection Framework

Author:

Pei Jiyuan1ORCID,Liu Jialin1ORCID,Mei Yi2ORCID

Affiliation:

1. Southern University of Science and Technology, Shenzhen, China

2. Victoria University of Wellington, Wellington, New Zealand

Funder

National Key R&D Program of China

National Natural Science Foundation of China

Shenzhen Science and Technology Program

Research Institute of Trustworthy Autonomous Systems

Guangdong Provincial Key Laboratory

Publisher

ACM

Reference45 articles.

1. Mehmet Emin Aydin Rafet Durgut and Abdur Rakib. 2023. Adaptive operator selection utilising generalised experience. arXiv:2401.05350 [cs.NE]

2. Zahra Beheshti and Siti Mariyam Hj Shamsuddin. 2013. A review of population-based meta-heuristic algorithms. International Journal of Advances in Soft Computing and its Applications 5, 1 (2013), 1--35.

3. Jieyi Bi, Yining Ma, Jiahai Wang, Zhiguang Cao, Jinbiao Chen, Yuan Sun, and Yeow Meng Chee. 2022. Learning generalizable models for vehicle routing problems via knowledge distillation. In Advances in Neural Information Processing Systems, Vol. 35. Curran Associates, Inc., 31226--31238.

4. Learning to optimize: a primer and a benchmark;Chen Tianlong;Journal of Machine Learning Research,2022

5. Tianlong Chen, Weiyi Zhang, Zhou Jingyang, Shiyu Chang, Sijia Liu, Lisa Amini, and Zhangyang Wang. 2020. Training stronger baselines for learning to optimize. In Advances in Neural Information Processing Systems, Vol. 33. Curran Associates, Inc., 7332--7343.

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