Runtime Analysis of a Multi-valued Compact Genetic Algorithm on Generalized OneMax

Author:

Adak SumitORCID,Witt CarstenORCID

Publisher

Springer Nature Switzerland

Reference37 articles.

1. Adak, S., Witt, C.: Runtime analysis of a multi-valued compact genetic algorithm on generalized OneMax (2024). https://arxiv.org/abs/2404.11239

2. Asoh, H., Mühlenbein, H.: On the mean convergence time of evolutionary algorithms without selection and mutation. In: Davidor, Y., Schwefel, H.-P., Männer, R. (eds.) Parallel Problem Solving from Nature — PPSN III, pp. 88–97. Springer, Berlin, Heidelberg (1994). https://doi.org/10.1007/3-540-58484-6_253

3. Baluja, S.: Population-based incremental learning: a method for integrating genetic search based function optimization and competitive learning. Carnegie Mellon University Pittsburgh, PA, School of Computer Science (1994)

4. Ben Jedidia, F., Doerr, B., Krejca, M.S.: Estimation-of-distribution algorithms for multi-valued decision variables. In: Proceedings of the Genetic and Evolutionary Computation Conference, pp. 230–238 (2023)

5. Benbaki, R., Benomar, Z., Doerr, B.: A rigorous runtime analysis of the 2-MMASIB on jump functions: ant colony optimizers can cope well with local optima. In: Proceedings of the Genetic and Evolutionary Computation Conference, pp. 4–13 (2021)

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