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» An Introduction to Evolutionary Programming
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CEC
2007
IEEE
15 years 6 months ago
Self-adaptation of mutation distribution in evolutionary algorithms
— This paper proposes a self-adaptation method to control not only the mutation strength parameter, but also the mutation distribution for evolutionary algorithms. For this purpo...
Renato Tinós, Shengxiang Yang
CEC
2005
IEEE
15 years 5 months ago
A simple hybrid evolutionary algorithm for finding Golomb rulers
Abstract- Finding Golomb rulers is an extremely challenging optimization problem (with many practical applications) that has been approached by a variety of search methods in recen...
Iván Dotú, Pascal Van Hentenryck
ATAL
2003
Springer
15 years 5 months ago
Integrating evolutionary computing and the SADDE methodology
This paper introduces a methodology to help the programmer in the transition from a set of desired global properties expressed as an equation-based model (EBM) that a Multi-Agent ...
Carles Sierra, Jordi Sabater, Jaume Agustí-...
HAIS
2009
Springer
15 years 4 months ago
Hybrid Evolutionary Algorithm for Solving Global Optimization Problems
Differential Evolution (DE) is a novel evolutionary approach capable of handling non-differentiable, non-linear and multi-modal objective functions. DE has been consistently ranked...
Radha Thangaraj, Millie Pant, Ajith Abraham, Youak...
AISB
1994
Springer
15 years 3 months ago
An Empirical Comparison of Selection Methods in Evolutionary Algorithms
Selection methods in Evolutionary Algorithms, including Genetic Algorithms, Evolution Strategies ES and Evolutionary Programming, EP are compared by observing the rate of converge...
Peter J. B. Hancock