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» Evolutionary multiobjective optimization
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AE
2005
Springer
15 years 10 months ago
Algorithms (X, sigma, eta): Quasi-random Mutations for Evolution Strategies
Randomization is an efficient tool for global optimization. We here define a method which keeps : – the order 0 of evolutionary algorithms (no gradient) ; – the stochastic as...
Anne Auger, Mohamed Jebalia, Olivier Teytaud
145
Voted
GECCO
2004
Springer
137views Optimization» more  GECCO 2004»
15 years 10 months ago
Evolving Better Multiple Sequence Alignments
Aligning multiple DNA or protein sequences is a fundamental step in the analyses of phylogeny, homology and molecular structure. Heuristic algorithms are applied because optimal mu...
Luke Sheneman, James A. Foster
NCA
2007
IEEE
15 years 4 months ago
Ensemble of hybrid neural network learning approaches for designing pharmaceutical drugs
Designing drugs is a current problem in the pharmaceutical research. By designing a drug we mean to choose some variables of drug formulation (inputs), for obtaining optimal charac...
Ajith Abraham, Crina Grosan, Stefan Tigan
AHS
2007
IEEE
210views Hardware» more  AHS 2007»
15 years 11 months ago
Evaluation of a New Platform For Image Filter Evolution
This paper describes a new FPGA implementation of a system for evolutionary image filter design. Three parallel search algorithms are compared. An optimal mutation rate and the q...
Zdenek Vasícek, Lukás Sekanina
EUROGP
1999
Springer
141views Optimization» more  EUROGP 1999»
15 years 9 months ago
Busy Beaver - The Influence of Representation
The Busy Beaver is an interesting theoretical problem proposed by Rado in 1962. In this paper we propose an evolutionary approach to this problem. We will focus on the representati...
Penousal Machado, Francisco Baptista Pereira, Am&i...