Nasser R. Sabar‘s (Queensland University of Technology, Brisbane) and Aldeida Aleti‘s (Faculty of Information Technology, Monash University, Melbourne) paper “An Adaptive Memetic Algorithm for the Architecture Optimisation Problem”  describes the combination of a local search and a genetic algorithm to generate memetic algorithms.
They implement an adaptive scheme to address problems caused by the trade-off between exploration and exploitation. The tuning of the hyper-parameter and parameter values was performed using a sequential parameter optimisation technique . A problem from the design of embedded systems (“component deployment”) is used to evaluate the performance. The test function tool is available online . Results indicate that the proposed memetic algorithm (AMA) performed better than the single algorithms.
 N. R. Sabar and A. Aleti. An adaptive memetic algorithm for the architecture optimisation problem. In M. Wagner, X. Li, and T. Hendtlass, editors, Artificial Life and Computational Intelligence: Third Australasian Conference, ACALCI 2017, Geelong, VIC, Australia, January 31 – February 2, 2017, Proceedings, pages 254–265, Cham, 2017. Springer International Publishing.
 Bartz-Beielstein, T., Lasarczyk, C., Preuss, M.: Sequential parameter optimization.
In: IEEE Congress on Evolutionary Computation, pp. 773–780. IEEE (2005). DOI: 10.1109/CEC.2005.1554761