Optimization of discrete data structures via combinatorial stirling numbers of the second kind
Shashikala Gurpurdirector@symlaw.ac.inSymbiosis Law SchoolSymbiosis Centre for Advanced Legal Studies and Research (SCALSAR), Symbiosis International (Deemed University)Pune, Maharashtra, 411014, IndiaView full profile → , *Sudhakar ReddyCorresponding authorr.sudhakar@jainuniversity.ac.inDepartment of PhysicsSchool of SciencesJAIN (Deemed-to-be University)Bengaluru, Karnataka, 560069, IndiaView full profile → , Gagan Tiwarigagan.tiwari@niu.edu.inDepartment of Computer SciencesNoida International UniversityNoida, Uttar Pradesh, 203201, IndiaView full profile → , Vaishali Rajputvaishali.rajput@vit.eduDepartment of Artificial Intelligence & Data ScienceVishwakarma Institute of TechnologyPune, Maharashtra, 411037, IndiaView full profile → , Ch. Phanindraphanindra@outlook.comDepartment of Computer Science & EngineeringKITS Akshar Institute of TechnologyGuntur, Andhra Pradesh, 522019, IndiaView full profile → , A. Suneethasuneetha@outlook.comDepartment of Computer Science and EngineeringKKR and KSR Institute of Technology and SciencesGuntur, Andhra Pradesh, 522017, IndiaView full profile →
* Corresponding author · click or hover a name for details
- Received:
- 07 May 2025
- Published Online:
- 31 Dec 2025
- Article type:
- Research Article
- Language:
- EN
- Article no.:
- JDMSC-2477
- Pages:
- 453–460
Abstract
Keywords
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References
[1] X. Yang, Z. Wang, H. Zhang, N. Ma, N. Yang, H. Liu, H. Zhang, and L. Yang, “A review: Machine learning for combinatorial optimization problems in energy areas,” Algorithms, vol. 15, no. 6, p. 205 (2022).
[2] N. Mazyavkina, S. Sviridov, S. Ivanov, and E. Burnaev, “Reinforcement learning for combinatorial optimization: A survey,” Comput. Oper. Res., vol. 134, p. 105400 (2021).
[3] Y. Bengio, A. Lodi, and A. Prouvost, “Machine learning for combinatorial optimization: A methodological tour d’horizon,” Eur. J. Oper. Res., vol. 290, no. 2, pp. 405–421 (2021).
[4] M. Karimi-Mamaghan, M. Mohammadi, P. Meyer, A. M. Karimi-Mamaghan, and E. G. Talbi, “Machine learning at the service of meta-heuristics for solving combinatorial optimization problems: A state-of-the-art,” Eur. J. Oper. Res., vol. 296, no. 2, pp. 393–422 (2022).
[5] M. H. Hadi and L. A. A. Jabar, “Build new operator using cluster system,” J. Interdiscip. Math., vol. 28, no. 3-B, pp. 1117–1124 (2025), doi: 10.47974/JIM-2088.
[6] S. T. Shirkande, S. Misal, S. Mhaske, A. Salunkhe, and D. Mendke, “Blockchain in supply chain management: A survey of emerging trends and next-generation solutions,” Int. J. Electr., Electron. Comput. Syst., vol. 13, no. 2, pp. 36–42 (2025).
[7] T. D. Barrett, C. W. F. Parsonson, and A. Laterre, “Learning to solve combinatorial graph partitioning problems via efficient exploration,” arXiv preprint, arXiv:2205.14105 [cs.LG] (2022).
[8] A. Z. Wagner, “Constructions in combinatorics via neural networks,” arXiv preprint, arXiv:2104.14516 [math.CO] (2021).
[9] J. Zhou, G. Cui, S. Hu, Z. Zhang, C. Yang, Z. Liu, L. Wang, C. Li, and M. Sun, “Graph neural networks: A review of methods and applications,” AI Open, vol. 1, pp. 57–81 (2020).
[10] E. Rosemaro, Anasica, and I. Zellar, “AI-based decision support systems for emergency medical services,” Int. J. Recent Adv. Eng. Technol., vol. 13, no. 1, pp. 7–12 (2025).
