Meta-heuristics meet sports: a systematic review from the viewpoint of nature inspired algorithms
Author:
Affiliation:
1. Department of Computer Science, Faculty of Applied Sciences , University of Sri Jayewardenepura , Nugegoda , Sri Lanka .
2. Department of Statistics, Faculty of Applied Sciences , University of Sri Jayewardenepura , Nugegoda , Sri Lanka .
Abstract
Publisher
Walter de Gruyter GmbH
Subject
Biomedical Engineering,General Computer Science
Link
https://www.sciendo.com/pdf/10.2478/ijcss-2022-0003
Reference129 articles.
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2. Ahmed, F., Deb, K., and Jindal, A. (2013). Multi-objective optimization and decision making approaches to cricket team selection. Applied Soft Computing, 13(1):402–414.
3. Ahmed, F., Jindal, A., and Deb, K. (2011b). Cricket team selection using evolutionary multi-objective optimization. In International Conference on Swarm, Evolutionary, and Memetic Computing, pages 71–78. Springer.10.1007/978-3-642-27242-4_9
4. Alavi, M. and Henderson, J. C. (1981). An evolutionary strategy for implementing a decision support system. Management science, 27(11):1309–1323.
5. Balaji, S., Karthikeyan, S., and Manikandan, R. (2021). Object detection using metaheuristic algorithm for volley ball sports application. Journal of Ambient Intelligence and Humanized Computing, 12(1):375–385.
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