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Solving NP-hard problems traditionally relies on heuristics, yet manually designing effective heuristics for complex problems remains a significant challenge.
Approximation algorithms for bin-packing—an updated survey
Edward G Coffman Jr, Michael R Garey, and David S Johnson. 1984 · 1984
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Asymptotically efficient adaptive allocation rules
T.L Lai and Herbert Robbins. 1985 · 1985
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Or-library: distributing test problems by electronic mail
John E. Beasley. 1990 · 1990
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Lower bounds and reduction procedures for the bin packing problem
Silvano Martello and Paolo Toth. 1990 · 1990
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Using confidence bounds for exploitation-exploration trade-offs
Peter Auer. 2002 · 2002
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Hyper-heuristics: An emerging direction in modern search technology
Edmund K. Burke, Graham Kendall, Jim Newall, Emma Hart, Peter Ross, and Sonia Schulenburg. 2003 · 2003
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Additive combinatorics , volume 105
Terence Tao and Van H Vu. 2006 · 2006
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Open issues in genetic programming
Michael O’Neill, Leonardo Vanneschi, Steven M. Gustafson, and Wolfgang Banzhaf. 2010 · 2010
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Guided local search
Christos Voudouris, Edward PK Tsang, and Abdullah Alsheddy. 2010 · 2010
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Attention, learn to solve routing problems!
Wouter Kool, Herke Van Hoof, and Max Welling. 2018 · 2018
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New applications of the polynomial method: the cap set conjecture and beyond
Joshua Grochow. 2019 · 2019
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Deep learning assisted heuristic tree search for the container pre-marshalling problem
André Hottung, Shunji Tanaka, and Kevin Tierney. 2020 · 2020
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Exploration strategies in deep reinforcement learning
Lilian Weng. 2020 · 2020
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Program synthesis with large language models
Jacob Austin, Augustus Odena, Maxwell Nye, Maarten Bosma, Henryk Michalewski, David Dohan, Ellen Jiang, Carrie Cai, Michael Terry, Quoc Le, et al. 2021 · 2021
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Machine learning for combinatorial optimization: A methodological tour d’horizon
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Evaluating large language models trained on code
Mark Chen, Jerry Tworek, Heewoo Jun, Qiming Yuan, Henrique Ponde De Oliveira Pinto, Jared Kaplan, Harri Edwards, Yuri Burda, Nicholas Joseph, Greg Brockman, et al. 2021 · 2021
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Graph neural network guided local search for the traveling salesperson problem
Benjamin Hudson, Qingbiao Li, Matthew Malencia, and Amanda Prorok. 2022 · 2022
Evoprompting: language models for code-level neural architecture search
Angelica Chen, David Dohan, and David So. 2024 · 2024
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Deepseek-coder: When the large language model meets programming - the rise of code intelligence
Daya Guo, Qihao Zhu, Dejian Yang, Zhenda Xie, Kai Dong, Wentao Zhang, Guanting Chen, Xiao Bi, Y. Wu, Y. K. Li, Fuli Luo, Yingfei Xiong, and Wenfeng Liang. 2024 · 2024
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Opencoder: The open cookbook for top-tier code large language models
Siming Huang, Tianhao Cheng, Jason Klein Liu, Jiaran Hao, Liuyihan Song, Yang Xu, J Yang, JH Liu, Chenchen Zhang, Linzheng Chai, et al. 2024 · 2024
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Evolution Through Large Models , pages 331–366
Joel Lehman, Jonathan Gordon, Shawn Jain, Kamal Ndousse, Cathy Yeh, and Kenneth O. Stanley. 2024 · 2024
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Evolution of heuristics: Towards efficient automatic algorithm design using large language model
Fei Liu, Tong Xialiang, Mingxuan Yuan, Xi Lin, Fu Luo, Zhenkun Wang, Zhichao Lu, and Qingfu Zhang. 2024 · 2024
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Learning heuristics with different representations for stochastic routing
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Starcoder: may the source be with you!
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Algorithm evolution using large language model
Fei Liu, Xialiang Tong, Mingxuan Yuan, and Qingfu Zhang. 2023 · 2023
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Explainable artificial intelligence by genetic programming: A survey
Yi Mei, Qi Chen, Andrew Lensen, Bing Xue, and Mengjie Zhang. 2023 · 2023
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Language model crossover: Variation through few-shot prompting
Elliot Meyerson, Mark J Nelson, Herbie Bradley, Adam Gaier, Arash Moradi, Amy K Hoover, and Joel Lehman. 2023 · 2023
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Can gpt-4 perform neural architecture search?
Mingkai Zheng, Xiu Su, Shan You, Fei Wang, Chen Qian, Chang Xu, and Samuel Albanie. 2023 · 2023
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Large language model-based evolutionary optimizer: Reasoning with elitism
Shuvayan Brahmachary, Subodh M Joshi, Aniruddha Panda, Kaushik Koneripalli, Arun Kumar Sagotra, Harshil Patel, Ankush Sharma, Ameya D Jagtap, and Kaushic Kalyanaraman. 2024 · 2024
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Llmatic: neural architecture search via large language models and quality diversity optimization
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Mathematical discoveries from program search with large language models
Bernardino Romera-Paredes, Mohammadamin Barekatain, Alexander Novikov, Matej Balog, M Pawan Kumar, Emilien Dupont, Francisco JR Ruiz, Jordan S Ellenberg, Pengming Wang, Omar Fawzi, et al. 2024 · 2024
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Efficient evolutionary search over chemical space with large language models
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Reevo: Large language models as hyper-heuristics with reflective evolution
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Understanding the importance of evolutionary search in automated heuristic design with large language models
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Sglang: Efficient execution of structured language model programs
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