Improved shuffled Frog leaping algorithm with unsupervised population partitioning strategies for complex optimization problems
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Publisher
Springer Science and Business Media LLC
Link
https://link.springer.com/content/pdf/10.1007/s10878-023-01102-w.pdf
Reference37 articles.
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2. Banati H, Mehta S (2013) Improved shuffled frog leaping algorithm for continuous optimisation adapted sevo toolbox. Int J Adv Intell Paradigms 5:31–44. https://doi.org/10.1504/IJAIP.2013.054670
3. Cai J, Zhou R, Lei D (2020) Dynamic shuffled frog-leaping algorithm for distributed hybrid flow shop scheduling with multiprocessor tasks. Eng Appl Artif Intell 90:103540. https://doi.org/10.1016/j.engappai.2020.103540
4. Cai J, Lei D, Li M (2020) A shuffled frog-leaping algorithm with memeplex quality for bi-objective distributed scheduling in hybrid flow shop. Int J Prod Res 59:1–18. https://doi.org/10.1080/00207543.2020.1780333
5. Chaudhary R, Banati H (2020) Study of population partitioning techniques on efficiency of swarm algorithms. Swarm Evol Comput 55:100672. https://doi.org/10.1016/j.swevo.2020.100672
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