Laplacian Salp Swarm Algorithm for continuous optimization
Author:
Funder
Ministry of Education, India
Publisher
Springer Science and Business Media LLC
Subject
Strategy and Management,Safety, Risk, Reliability and Quality
Link
https://link.springer.com/content/pdf/10.1007/s13198-023-01935-y.pdf
Reference43 articles.
1. Abusnaina AA, Ahmad S, Jarrar R, Mafarja M (2018) Training neural networks using Salp Swarm Algorithm for pattern classification. In: Proceedings of the 2nd international conference on future networks and distributed systems. https://doi.org/10.1145/3231053.3231070
2. Aljarah I, Mafarja M, Heidari AA (2018) Asynchronous accelerating multi-leader salp chains for feature selection. Appl Soft Comput J 71:964–979
3. Allah R, Hassanien AE, Elhoseny M, Gunasekaran M (2018) A new Binary Salp Swarm Algorithm: development and application for optimization tasks. Neural Comput Appl 31:1–23
4. Bakrawy LME (2020) An adaptive optimization algorithm based on modified whale optimization algorithm and Laplace crossover. Int J Metaheuris 7(3):284–305
5. Bansal JC, Deep K, Veeramachaneni K, Osadciw L (2009) Information sharing strategy among particles in Particle Swarm Optimization using Laplacian operator. In: 2009 IEEE swarm intelligence symposium, pp 30–36. https://doi.org/10.1109/SIS.2009.4937841
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