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GECCO
2007
Springer
182views Optimization» more  GECCO 2007»
16 years 26 days ago
An analysis of the effects of population structure on scalable multiobjective optimization problems
Multiobjective evolutionary algorithms (MOEA) are an effective tool for solving search and optimization problems containing several incommensurable and possibly conflicting objec...
Michael Kirley, Robert L. Stewart
GECCO
2007
Springer
186views Optimization» more  GECCO 2007»
16 years 26 days ago
Knowledge reuse in genetic programming applied to visual learning
We propose a method of knowledge reuse for an ensemble of genetic programming-based learners solving a visual learning task. First, we introduce a visual learning method that uses...
Wojciech Jaskowski, Krzysztof Krawiec, Bartosz Wie...
GECCO
2007
Springer
157views Optimization» more  GECCO 2007»
16 years 26 days ago
A doubly distributed genetic algorithm for network coding
We present a genetic algorithm which is distributed in two novel ways: along genotype and temporal axes. Our algorithm first distributes, for every member of the population, a su...
Minkyu Kim, Varun Aggarwal, Una-May O'Reilly, Muri...
GECCO
2007
Springer
155views Optimization» more  GECCO 2007»
16 years 26 days ago
Towards billion-bit optimization via a parallel estimation of distribution algorithm
This paper presents a highly efficient, fully parallelized implementation of the compact genetic algorithm (cGA) to solve very large scale problems with millions to billions of va...
Kumara Sastry, David E. Goldberg, Xavier Llor&agra...
GECCO
2007
Springer
176views Optimization» more  GECCO 2007»
16 years 26 days ago
Two-level of nondominated solutions approach to multiobjective particle swarm optimization
In multiobjective particle swarm optimization (MOPSO) methods, selecting the local best and the global best for each particle of the population has a great impact on the convergen...
M. A. Abido