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» GAS, A Concept on Modeling Species in Genetic Algorithms
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BMCBI
2007
157views more  BMCBI 2007»
13 years 7 months ago
A hybrid multiscale Monte Carlo algorithm (HyMSMC) to cope with disparity in time scales and species populations in intracellula
Background: The fundamental role that intrinsic stochasticity plays in cellular functions has been shown via numerous computational and experimental studies. In the face of such e...
Asawari Samant, Babatunde A. Ogunnaike, Dionisios ...
GECCO
2008
Springer
179views Optimization» more  GECCO 2008»
13 years 8 months ago
ASAGA: an adaptive surrogate-assisted genetic algorithm
Genetic algorithms (GAs) used in complex optimization domains usually need to perform a large number of fitness function evaluations in order to get near-optimal solutions. In rea...
Liang Shi, Khaled Rasheed
GECCO
2004
Springer
175views Optimization» more  GECCO 2004»
14 years 22 days ago
Enhanced Innovation: A Fusion of Chance Discovery and Evolutionary Computation to Foster Creative Processes and Decision Making
Abstract. Human-based genetic algorithms are powerful tools for organizational modeling. If we enhance them using chance discovery techniques, we obtain an innovative approach for ...
Xavier Llorà, Kei Ohnishi, Ying-Ping Chen, ...
ACRI
2008
Springer
14 years 1 months ago
Automatic Design of FPGA Processor for the Backtracking of DNA Sequences Evolution Using Cellular Automata and Genetic Algorithm
In several cases, the DNA sequences of an organism are available in different stages of its evolution and it is desirable to reconstruct the DNA sequence in a previous evolution st...
Georgios Ch. Sirakoulis
PPSN
1992
Springer
13 years 11 months ago
Nonstationary Function Optimization using the Structured Genetic Algorithm
In this paper, we describe the application of a new type of genetic algorithm called the Structured Genetic Algorithm (sGA) for function optimization in nonstationary environments...
Dipankar Dasgupta, Douglas R. McGregor