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129
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GECCO
2006
Springer
206views Optimization» more  GECCO 2006»
15 years 7 months ago
Adaptive discretization for probabilistic model building genetic algorithms
This paper proposes an adaptive discretization method, called Split-on-Demand (SoD), to enable the probabilistic model building genetic algorithm (PMBGA) to solve optimization pro...
Chao-Hong Chen, Wei-Nan Liu, Ying-Ping Chen
GECCO
2006
Springer
188views Optimization» more  GECCO 2006»
15 years 7 months ago
Dynamic multi-objective optimization with evolutionary algorithms: a forward-looking approach
This work describes a forward-looking approach for the solution of dynamic (time-changing) problems using evolutionary algorithms. The main idea of the proposed method is to combi...
Iason Hatzakis, David Wallace
137
Voted
GECCO
2006
Springer
138views Optimization» more  GECCO 2006»
15 years 7 months ago
Does overfitting affect performance in estimation of distribution algorithms
Estimation of Distribution Algorithms (EDAs) are a class of evolutionary algorithms that use machine learning techniques to solve optimization problems. Machine learning is used t...
Hao Wu, Jonathan L. Shapiro
125
Voted
GECCO
2006
Springer
159views Optimization» more  GECCO 2006»
15 years 7 months ago
Identification of weak motifs in multiple biological sequences using genetic algorithm
Recognition of motifs in multiple unaligned sequences provides an insight into protein structure and function. The task of discovering these motifs is very challenging because mos...
Topon Kumar Paul, Hitoshi Iba
GECCO
2006
Springer
182views Optimization» more  GECCO 2006»
15 years 7 months ago
Distributed genetic algorithm for energy-efficient resource management in sensor networks
In this work we consider energy-efficient resource management in an environment monitoring and hazard detection sensor network. Our goal is to allocate different detection methods...
Qinru Qiu, Qing Wu, Daniel J. Burns, Douglas Holzh...