Estimation of Distribution Algorithms: A New Tool for Evolutionary Computation
Estimation of Distribution Algorithms: A New Tool for Evolutionary Computation
Journal of Global Optimization
Finding Global Minima with a Computable Filled Function
Journal of Global Optimization
From Recombination of Genes to the Estimation of Distributions I. Binary Parameters
PPSN IV Proceedings of the 4th International Conference on Parallel Problem Solving from Nature
Introduction to Stochastic Search and Optimization
Introduction to Stochastic Search and Optimization
A New Filled Function Method for Global Optimization
Journal of Global Optimization
Small-World optimization algorithm for function optimization
ICNC'06 Proceedings of the Second international conference on Advances in Natural Computation - Volume Part II
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In this paper a new global optimization algorithm for real valued functions, MAGO, is introduced. MAGO (Multi Dynamics Algorithm for Global Optimization) has been inspired by ideas from Estimation of Distribution Algorithms, Differential Evolution Algorithms and Statistical Quality Control. MAGO makes use of three different population dynamics: a changing uniform distribution to explore the searching space, a mechanism of propagating differences related to the best individuals, and a strategy for diversity preservation. Only the population size and the number of generations must be provided by the final user. The algorithm's success in achieving global optima in the presence of multimodality has been shown through its application on a set of standard test functions.