@inproceedings{1377db60614b4cac804a05b41acd5e5d,
title = "Hybridizing genetic algorithm with cross entropy for solving continuous functions",
abstract = "In this paper, a metaheuristic that combines a Genetic Algorithm and a Cross Entropy Algorithm is presented. The aim of this work is to achieve a synergy between the capabilities of the algorithms using different population sizes in order to obtain the closest value to the optimal of the function. The proposal is applied to 12 benchmark functions with different characteristics, using different configurations.",
keywords = "Algorithms, Cross entropy, Experimentation, Genetic algorithm, Hybridization technique, Meta-heuristic, Optimization problem, Real-world problem",
author = "Pedro Lopez-Garcia and Enrique Onieva and Eneko Osaba and Masegosa, \{Antonio D.\} and Asier Perallos",
year = "2015",
month = jul,
day = "11",
doi = "10.1145/2739482.2764881",
language = "English",
series = "GECCO 2015 - Companion Publication of the 2015 Genetic and Evolutionary Computation Conference",
publisher = "Association for Computing Machinery, Inc",
pages = "763--764",
editor = "Sara Silva",
booktitle = "GECCO 2015 - Companion Publication of the 2015 Genetic and Evolutionary Computation Conference",
note = "17th Genetic and Evolutionary Computation Conference, GECCO 2015 ; Conference date: 11-07-2015 Through 15-07-2015",
}