Abstract
For the last decades, metaheuristics have become ever more popular as a tool to solve a large class of difficult optimization problems. However, determining the best configuration of a metaheuristic, which includes the program flow and the parameter settings, remains a difficult task. Adaptive metaheuristics (that change their configuration during the search) and multilevel metaheuristics (that change their configuration during the search by means of a metaheuristic) can be a solution for this. This chapter intends to make a quick review of the latest trends in adaptive metaheuristics and in multilevel metaheuristics.
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Sevaux, M., Sörensen, K., Pillay, N. (2018). Adaptive and Multilevel Metaheuristics. In: Martí, R., Pardalos, P., Resende, M. (eds) Handbook of Heuristics. Springer, Cham. https://doi.org/10.1007/978-3-319-07124-4_16
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