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MICRO
1990
IEEE
147views Hardware» more  MICRO 1990»
13 years 11 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
CPHYSICS
2006
204views more  CPHYSICS 2006»
13 years 7 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
GECCO
2006
Springer
171views Optimization» more  GECCO 2006»
13 years 11 months ago
A hybrid genetic search for multiple sequence alignment
This paper proposes a hybrid genetic algorithm for multiple sequence alignment. The algorithm evolves guide sequences and aligns input sequences based on the guide sequences. It a...
Seung-Hyun Moon, Sung-Soon Choi, Byung Ro Moon
GECCO
2008
Springer
133views Optimization» more  GECCO 2008»
13 years 8 months ago
The micro-genetic operator in the search of global trends
This work studies the mGA operator (Micro Genetic Algorithm), that has been proposed in literature as a “local search” operator for optimization with Genetic Algorithm. A new ...
Flávio V. C. Martins, Eduardo G. Carrano, E...
PATAT
2004
Springer
141views Education» more  PATAT 2004»
14 years 1 months ago
A Hybrid Multi-objective Evolutionary Algorithm for the Uncapacitated Exam Proximity Problem
A hybrid Multi-Objective Evolutionary Algorithm is used to tackle the uncapacitated exam proximity problem. In this hybridization, local search operators are used instead of the tr...
Pascal Côté, Tony Wong, Robert Sabour...