[1] Talbi, E. G. (2009). Metaheuristics: from design to implementation. John Wiley & Sons.

[2] Pillay, N., & Qu, R. (Eds.). (2021). Automated Design of Machine Learning and Search Algorithms. Berlin/Heidelberg, Germany: Springer.

[3] Burke, E. K., Courtois, T., Hyde, M., Kendall, G., Ochoa, G., Petrovic, S., & Vázquez-Rodríguez, J. A. (2009, August). Hyflex: A flexible framework for the design and analysis of hyper-heuristics. In Multidisciplinary International Scheduling Conference (MISTA 2009), Dublin, Ireland (pp. 790-797).

[4] Ochoa, G., Hyde, M., Curtois, T., Vazquez-Rodriguez, J. A., Walker, J., Gendreau, M., ... & Burke, E. K. (2012). Hyflex: A benchmark framework for cross-domain heuristic search. In Evolutionary Computation in Combinatorial Optimization: 12th European Conference, EvoCOP 2012, Málaga, Spain, April 11-13, 2012. Proceedings 12 (pp. 136-147). Springer Berlin Heidelberg.

[5] Burke, E. K., Gendreau, M., Hyde, M., Kendall, G., Ochoa, G., Özcan, E., & Qu, R. (2013). Hyper-heuristics: A survey of the state of the art. Journal of the Operational Research Society, 64(12), 1695-1724.

[6] Adriaensen, S., Ochoa, G., & Nowé, A. (2015, May). A benchmark set extension and comparative study for the hyflex framework. In 2015 IEEE Congress on Evolutionary Computation (CEC) (pp. 784-791). IEEE.

[7] Zhao, Q., Duan, Q., Yan, B., Cheng, S., & Shi, Y. (2023). Automated design of metaheuristic algorithms: A survey. arXiv preprint arXiv:2303.06532.

[8] Chen, T., Chen, X., Chen, W., Heaton, H., Liu, J., Wang, Z., & Yin, W. (2022). Learning to optimize: A primer and a benchmark. Journal of Machine Learning Research, 23(189), 1-59.

[9] Tang, K., & Yao, X. (2024). Learn to Optimize-A Brief Overview. National Science Review, nwae132.

[10] Kletzander, L., & Musliu, N. (2023, June). Large-state reinforcement learning for hyper-heuristics. In Proceedings of the AAAI Conference on Artificial Intelligence (Vol. 37, No. 10, pp. 12444-12452).