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162
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GECCO
2010
Springer
244views Optimization» more  GECCO 2010»
15 years 2 months ago
Implicit fitness and heterogeneous preferences in the genetic algorithm
This paper takes an economic approach to derive an evolutionary learning model based entirely on the endogenous employment of genetic operators in the service of self-interested a...
Justin T. H. Smith
107
Voted
GECCO
2006
Springer
179views Optimization» more  GECCO 2006»
15 years 6 months ago
Local search for multiobjective function optimization: pareto descent method
Genetic Algorithm (GA) is known as a potent multiobjective optimization method, and the effectiveness of hybridizing it with local search (LS) has recently been reported in the li...
Ken Harada, Jun Sakuma, Shigenobu Kobayashi
242
Voted
CP
2009
Springer
16 years 3 months ago
Coalition Structure Generation Utilizing Compact Characteristic Function Representations
This paper presents a new way of formalizing the Coalition Structure Generation problem (CSG), so that we can apply constraint optimization techniques to it. Forming effective coal...
Naoki Ohta, Vincent Conitzer, Ryo Ichimura, Yuko S...
128
Voted
CEC
2008
IEEE
15 years 9 months ago
High-level synthesis with multi-objective genetic algorithm: A comparative encoding analysis
— The high-level synthesis process involves three interdependent and NP-complete optimization problems: (i) the operation scheduling, (ii) the resource allocation, and (iii) the ...
Christian Pilato, Daniele Loiacono, Fabrizio Ferra...
109
Voted
SBRN
2000
IEEE
15 years 7 months ago
Evolutionary Optimization of RBF Networks
One of the main obstacles to the widespread use of artijcial neural networks is the difJiculty of adequately define valuesfor their free parameters. This article discusses how Rad...
Estefane G. M. de Lacerda, Teresa Bernarda Ludermi...