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Large language models (LLMs) have demonstrated exceptional performance not only in natural language processing tasks but also in a great variety of non-linguistic domains.
1903
Earlier work this paper cites.
1910
Earlier work this paper cites.
B. Gavish and S. C. Graves, “The travelling salesman problem and related problems,” 1978
1978
Earlier work this paper cites.
D. BHANDARI, C. A. MURTHY, and S. K. PAL, “GENETIC ALGORITHM WITH ELITIST MODEL AND ITS CONVERGENCE,” International Journal of Pattern Recognition and Artificial Intelligence , vol. 10, no. 06, pp. 731–747, 1996, _eprint: https://doi.org/10.1142/S0218001496000438. [Online]. Available: https://doi.org/10.1142/S0218001496000438
1996
Earlier work this paper cites.
D. Applegate and W. Cook, “Concorde tsp solver,” 2006. [Online]. Available: http://www.math.uwaterloo.ca/tsp/concorde/index.html
2006
Earlier work this paper cites.
S. Goyal, “A survey on travelling salesman problem,” in Midwest instruction and computing symposium , 2010, pp. 1–9
2010
Earlier work this paper cites.
M. Jamil and X.-S. Yang, “A literature survey of benchmark functions for global optimisation problems,” International Journal of Mathematical Modelling and Numerical Optimisation , vol. 4, no. 2, pp. 150–194, 2013
2013
Earlier work this paper cites.
P. Toth and D. Vigo, Vehicle routing: problems, methods, and applications . SIAM, 2014
2014
Earlier work this paper cites.
N. Hansen, D. V. Arnold, and A. Auger, “Evolution strategies,” Springer handbook of computational intelligence , pp. 871–898, 2015
2015
Earlier work this paper cites.
J. K. Pugh, L. B. Soros, and K. O. Stanley, “Quality diversity: A new frontier for evolutionary computation,” Frontiers in Robotics and AI , vol. 3, p. 202845, 2016
2016
Earlier work this paper cites.
A. Gupta, Y.-S. Ong, and L. Feng, “Multifactorial Evolution: Toward Evolutionary Multitasking,” IEEE Transactions on Evolutionary Computation , vol. 20, no. 3, pp. 343–357, Jun. 2016
2016
Earlier work this paper cites.
2018
Earlier work this paper cites.
A. Holtzman, J. Buys, L. Du, M. Forbes, and Y. Choi, “The curious case of neural text degeneration,” in International Conference on Learning Representations , 2020. [Online]. Available: https://openreview.net/forum?id=rygGQyrFvH
2020
Earlier work this paper cites.
2021
Earlier work this paper cites.
K. C. Tan, L. Feng, and M. Jiang, “Evolutionary Transfer Optimization - A New Frontier in Evolutionary Computation Research,” IEEE Computational Intelligence Magazine , vol. 16, no. 1, pp. 22–33, Feb. 2021
2021
Earlier work this paper cites.
M. N. Omidvar, X. Li, and X. Yao, “A review of population-based metaheuristics for large-scale black-box global optimization—part i,” IEEE Transactions on Evolutionary Computation , vol. 26, no. 5, pp. 802–822, 2022
2022
Earlier work this paper cites.
——, “A review of population-based metaheuristics for large-scale black-box global optimization—part ii,” IEEE Transactions on Evolutionary Computation , vol. 26, no. 5, pp. 823–843, 2022
2022
Earlier work this paper cites.
Z.-H. Zhan, L. Shi, K. C. Tan, and J. Zhang, “A survey on evolutionary computation for complex continuous optimization,” Artificial Intelligence Review , vol. 55, no. 1, pp. 59–110, Jan. 2022. [Online]. Available: https://doi.org/10.1007/s10462-021-10042-y
2022
Cited alongside, same era.
H. Xu, Y. Chen, Y. Du, N. Shao, W. Yanggang, H. Li, and Z. Yang, “Gps: Genetic Prompt Search for Efficient Few-Shot Learning,” in Proceedings of the 2022 Conference on Empirical Methods in Natural Language Processing , 2022, pp. 8162–8171
2022
Cited alongside, same era.
2023
Cited alongside, same era.
2023
Later among the works it cites.
J. Liang, X. Ban, K. Yu, B. Qu, K. Qiao, C. Yue, K. Chen, and K. C. Tan, “A Survey on Evolutionary Constrained Multiobjective Optimization,” IEEE Transactions on Evolutionary Computation , vol. 27, no. 2, pp. 201–221, 2023
2023
Later among the works it cites.
2023
Later among the works it cites.
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2023
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2023
Cited alongside, same era.
2023
Cited alongside, same era.
A. J. Thirunavukarasu, D. S. J. Ting, K. Elangovan, L. Gutierrez, T. F. Tan, and D. S. W. Ting, “Large language models in medicine,” Nature Medicine , vol. 29, no. 8, pp. 1930–1940, Aug. 2023, number: 8 Publisher: Nature Publishing Group. [Online]. Available: https://www.nature.com/articles/s41591-023-02448-8
2023
Cited alongside, same era.
D. A. Boiko, R. MacKnight, B. Kline, and G. Gomes, “Autonomous chemical research with large language models,” Nature , vol. 624, no. 7992, pp. 570–578, Dec. 2023, number: 7992 Publisher: Nature Publishing Group. [Online]. Available: https://www.nature.com/articles/s41586-023-06792-0
2023
Cited alongside, same era.
2023
Cited alongside, same era.
2023
Cited alongside, same era.
2023
Cited alongside, same era.
2023
Cited alongside, same era.
2023
Later among the works it cites.
2023
Later among the works it cites.
J. Lehman, J. Gordon, S. Jain, K. Ndousse, C. Yeh, and K. O. Stanley, “Evolution through large models,” in Handbook of Evolutionary Machine Learning . Springer, 2023, pp. 331–366
2023
Later among the works it cites.
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F. Liu, X. Tong, M. Yuan, X. Lin, F. Luo, Z. Wang, Z. Lu, and Q. Zhang, “Evolution of Heuristics: Towards Efficient Automatic Algorithm Design Using Large Language Model,” in Proceedings of the 41st International Conference on Machine Learning , 2024, pp. 1–9
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