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106
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GECCO
2007
Springer
276views Optimization» more  GECCO 2007»
15 years 6 months ago
Meta-optimizing semantic evolutionary search
I present MOSES (meta-optimizing semantic evolutionary search), a new probabilistic modeling (estimation of distribution) approach to program evolution. Distributions are not esti...
Moshe Looks
KES
1999
Springer
15 years 4 months ago
Dynamic Demes parallel genetic algorithm
Abstract—Dynamic Demes is a new method for the parallelisation of evolutionary algorithms. It was derived as a combination of two other parallelisation algorithms: the master-sla...
Mariusz Nowostawski, Riccardo Poli
98
Voted
CEC
2009
IEEE
15 years 7 months ago
An evaluation of Differential Evolution in software test data generation
— One of the main tasks software testing involves is the generation of the test inputs to be used during the test. Due to its expensive cost, the automation of this task has beco...
Ricardo Landa Becerra, Ramón Sagarna, Xin Y...
106
Voted
RSA
2002
99views more  RSA 2002»
15 years 6 days ago
Distributed algorithms with dynamical random transitions
Given any measure-preserving dynamical system (Y, A , , T) and g Lp() , we study convergence of the sequence 1 n n k=1 g TSk , n 1 where Sk is a dynamic Zr -valued random w...
Nadine Guillotin-Plantard, René Schott
120
Voted
CEC
2008
IEEE
15 years 7 months ago
Auto-tuning fuzzy granulation for evolutionary optimization
—Much of the computational complexity in employing evolutionary algorithms as optimization tool is due to the fitness function evaluation that may either not exist or be computat...
Mohsen Davarynejad, Mohammad R. Akbarzadeh-Totonch...