Search-Based Testing

Author:

Parsa Saeed

Publisher

Springer International Publishing

Reference34 articles.

1. Hassan, A., Almohammadi, K., Alkafaween, E., Hammouri, E.A.A., Surya Prasath, V.B.: Choosing mutation and crossover ratios for genetic algorithms—a review with a new dynamic approach. Information 10, 390 (2019). doi:https://doi.org/10.3390/info10120390

2. Renders, J., Flasse, S.P.: Hybrid methods using genetic algorithms for global optimization. IEEE Trans. Syst. Man, Cybern. B Cybern. 26, 243–258 (1996)

3. Vavak, F., Fogarty, C.: Comparison of steady-state and generational genetic algorithms for use in nonstationary environments. In: Proceedings of the IEEE International Conference on Evolutionary Computation, Nagoya, Japan, pp. 192–195 (1996)

4. Chaiyaratana, N., Zalzala, A.: Hybridisation of neural networks and genetic algorithms for time-optimal control. In: Proceedings of the 1999 Congress on Evolutionary Computation-CEC99 (Cat. No. 99TH8406), Washington, DC, USA (1999)

5. Man, F.K., Tang, S.K., Kwong, S.: Genetic Algorithms: Concepts and Designs. Springer, Berlin/Heidelberg, Germany (1999)

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