A Behavioural Study of the Crossover Operator in Diploid Genetic Algorithms
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Publisher
Springer International Publishing
Link
http://link.springer.com/content/pdf/10.1007/978-3-030-57802-2_8
Reference19 articles.
1. Bhasin, H., Behal, G., Aggarwal, N., Saini, R.K., Choudhary, S.: On the applicability of diploid genetic algorithms in dynamic environments. Soft Comput. 20(9), 3403–3410 (2016). https://doi.org/10.1007/s00500-015-1803-5
2. Bull, L.: Haploid-diploid evolutionary algorithms: the Baldwin effect and recombination nature’s way. In: AISB (2017)
3. Cobb, H.G., Grefenstette, J.J.: Genetic algorithms for tracking changing environments. Technical report, Naval Research Lab Washington DC (1993)
4. Digalakis, J., Margaritis, K.: On benchmarking functions for genetic algorithms. Int. J. Comput. Math. 77(4), 481–506 (2001). https://doi.org/10.1080/00207160108805080
5. Dulebenets, M.A.: A diploid evolutionary algorithm for sustainable truck scheduling at a cross-docking facility. Sustainability 10(5), 1333 (2018)
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