Abstract
Cuckoo search algorithm (CSA) experiences an upsurge in popularity since its invention due to its effectiveness in solving optimization problems. In this paper, a new CSA was proposed, in which the two-parent crossover operator was integrated in order to alleviate the deficiency of lack of information exchange. In addition, an adaptive step size strategy was introduced. The resultant algorithm was validated on optimizing benchmarking functions and a real-world problem. The experimental analysis highlighted the faster convergence ability of the proposed algorithm to the optimal solution.
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Ong, P., Zainuddin, Z., Sia, C.K., Zain, B.A.M. (2015). Adaptive Cuckoo Search Algorithm with Two-Parent Crossover for Solving Optimization Problems. In: Tan, Y., Shi, Y., Buarque, F., Gelbukh, A., Das, S., Engelbrecht, A. (eds) Advances in Swarm and Computational Intelligence. ICSI 2015. Lecture Notes in Computer Science(), vol 9140. Springer, Cham. https://doi.org/10.1007/978-3-319-20466-6_45
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DOI: https://doi.org/10.1007/978-3-319-20466-6_45
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