Memetic Algorithms with Local Search Chains in R: The Rmalschains Package Bergmeir, Christoph Norbert Molina Cabrera, Daniel Benítez Sánchez, José Manuel Continuous optimization Memetic algorithms MA-LS-Chains R (Software) Rmalschains Global optimization is an important field of research both in mathematics and computer sciences. It has applications in nearly all fields of modern science and engineering. Memetic algorithms are powerful problem solvers in the domain of continuous optimization, as they offer a trade-off between exploration of the search space using an evolutionary algorithm scheme, and focused exploitation of promising regions with a local search algorithm. In particular, we describe the memetic algorithms with local search chains (MA-LS-Chains) paradigm, and the R package Rmalschains, which implements them. MA-LS-Chains has proven to be effective compared to other algorithms, especially in high-dimensional problem solving. In an experimental study, we demonstrate the advantages of using Rmalschains for high-dimension optimization problems in comparison to other optimization methods already available in R. 2017-03-13T08:59:36Z 2017-03-13T08:59:36Z 2016 info:eu-repo/semantics/article Bergmeir, C.N.; Molina, D.; Benítez Sánchez, J.M. Memetic Algorithms with Local Search Chains in R: The Rmalschains Package. Journal of Statistical Software, 75(4): 1-33 (2016). [http://hdl.handle.net/10481/45215] 1548-7660 http://hdl.handle.net/10481/45215 10.18637/jss.v075.i04 eng http://creativecommons.org/licenses/by-nc-nd/3.0/ info:eu-repo/semantics/openAccess Creative Commons Attribution-NonCommercial-NoDerivs 3.0 License American Statistical Association