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Stock index return forecasting: semantics-based genetic programming with local search optimiser., , , and . Int. J. Bio Inspired Comput., 10 (3): 159-171 (2017)The effect of selection from old populations in genetic algorithms., , and . GECCO (Companion), page 161-162. ACM, (2011)Introduction: special issue on parallel and distributed evolutionary algorithms, part I., and . Genet. Program. Evolvable Mach., 10 (4): 339-341 (2009)Fitness-proportional negative slope coefficient as a hardness measure for genetic algorithms., and . GECCO, page 1335-1342. ACM, (2007)A study of search algorithms' optimization speed., , and . J. Comb. Optim., 27 (2): 256-270 (2014)Evolutionary Computation: A Brief Overview., and . Genetic and Evolutionary Computation: Medical Applications, Wiley, (2011)Geometric Semantic Genetic Programming for Real Life Applications., , , and . GPTP, page 191-209. Springer, (2013)A Distance Between Populations for n-Points Crossover in Genetic Algorithms., , , and . CoRR, (2017)Theory and Practice for Efficient Genetic Programming. Faculty of Sciences, University of Lausanne, Switzerland, (2004)Negative Slope Coefficient. A Measure to Characterize Genetic Programming, , , and . Proceedings of the 9th European Conference on Genetic Programming, volume 3905 of Lecture Notes in Computer Science, page 178--189. Budapest, Hungary, Springer, (10 - 12 April 2006)