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CPHYSICS
2006
204views more  CPHYSICS 2006»
15 years 2 months ago
Genetically controlled random search: a global optimization method for continuous multidimensional functions
A new stochastic method for locating the global minimum of a multidimensional function inside a rectangular hyperbox is presented. A sampling technique is employed that makes use ...
Ioannis G. Tsoulos, Isaac E. Lagaris
LCTRTS
1999
Springer
15 years 6 months ago
Optimizing for Reduced Code Space using Genetic Algorithms
Code space is a critical issue facing designers of software for embedded systems. Many traditional compiler optimizations are designed to reduce the execution time of compiled cod...
Keith D. Cooper, Philip J. Schielke, Devika Subram...
GECCO
2007
Springer
558views Optimization» more  GECCO 2007»
15 years 8 months ago
A chain-model genetic algorithm for Bayesian network structure learning
Bayesian Networks are today used in various fields and domains due to their inherent ability to deal with uncertainty. Learning Bayesian Networks, however is an NP-Hard task [7]....
Ratiba Kabli, Frank Herrmann, John McCall
111
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MICRO
1990
IEEE
147views Hardware» more  MICRO 1990»
15 years 6 months ago
Motivation and framework for using genetic algorithms for microcode compaction
Genetic algorithms are a robust adaptive optimization technique based on a biological paradigm. They perform efficient search on poorly-defined spaces by maintaining an ordered po...
Steven J. Beaty, Darrell Whitley, Gearold Johnson
GECCO
2008
Springer
165views Optimization» more  GECCO 2008»
15 years 3 months ago
Multiple sequence alignment using a GLOCSA guided genetic algorithm
This paper introduces GLOCSA as a new scoring function to rate multiple sequence alignments. It is intended to be simple, considering the whole alignment at once and reflecting t...
Edgar David Arenas-Díaz, Helga Ochoterena-B...