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GECCO
2008
Springer
155views Optimization» more  GECCO 2008»
15 years 8 months ago
Integrating user preferences with particle swarms for multi-objective optimization
This paper proposes a method to use reference points as preferences to guide a particle swarm algorithm to search towards preferred regions of the Pareto front. A decision maker c...
Upali K. Wickramasinghe, Xiaodong Li
190
Voted
GECCO
2007
Springer
194views Optimization» more  GECCO 2007»
16 years 1 months ago
Hybrid coevolutionary algorithms vs. SVM algorithms
As a learning method support vector machine is regarded as one of the best classifiers with a strong mathematical foundation. On the other hand, evolutionary computational techniq...
Rui Li, Bir Bhanu, Krzysztof Krawiec
148
Voted
CEC
2005
IEEE
16 years 14 days ago
A population-based, steady-state procedure for real-parameter optimization
Despite the existence of a number of procedures for real-parameter optimization using evolutionary algorithms, there is still a need of a systematic and unbiased comparison of diï...
Ankur Sinha, Santosh Tiwari, Kalyanmoy Deb
184
Voted
EMO
2005
Springer
120views Optimization» more  EMO 2005»
16 years 12 days ago
Multiobjective Optimization on a Budget of 250 Evaluations
Abstract. In engineering and other ‘real-world’ applications, multiobjective optimization problems must frequently be tackled on a tight evaluation budget — tens or hundreds ...
Joshua D. Knowles, Evan J. Hughes
IAT
2003
IEEE
16 years 4 days ago
Classification Rule Discovery with Ant Colony Optimization
—Ant-based algorithms or ant colony optimization (ACO) algorithms have been applied successfully to combinatorial optimization problems. More recently, Parpinelli and colleagues ...
Bo Liu, Hussein A. Abbass, Bob McKay