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» Multiobjective Evolutionary Algorithms: Analyzing the State-...
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CEC
2007
IEEE
14 years 18 days ago
Plateaus can be harder in multi-objective optimization
—In recent years a lot of progress has been made in understanding the behavior of evolutionary computation methods for single- and multi-objective problems. Our aim is to analyze...
Tobias Friedrich, Nils Hebbinghaus, Frank Neumann
GECCO
2005
Springer
197views Optimization» more  GECCO 2005»
13 years 11 months ago
Performance assessment of an artificial immune system multiobjective optimizer by two improved metrics
In this study, we introduce two improved assessment metrics of multiobjective optimizers, Nondominated Ratio and Spacing Distribution, and analyze their rationality and validity. ...
Maoguo Gong, Licheng Jiao, Haifeng Du, Ronghua Sha...
EC
2010
158views ECommerce» more  EC 2010»
13 years 3 months ago
An Efficient Algorithm for Computing Hypervolume Contributions
The hypervolume indicator serves as a sorting criterion in many recent multi-objective evolutionary algorithms (MOEAs). Typical algorithms remove the solution with the smallest lo...
Karl Bringmann, Tobias Friedrich
SACI
2007
IEEE
14 years 16 days ago
A Computational Intelligence Approach for Ranking Risk Factors in Preterm Birth
- The aim of this paper is to propose a filter, based on a multi-objective evolutionary algorithm, for attributes’ ranking in the context of a data mining task. The behavior of t...
Daniela Zaharie, Stefan Holban, Diana Lungeanu, Da...
ISICA
2007
Springer
14 years 12 days ago
On the Performance of Metamodel Assisted MOEA/D
Abstract. MOEA/D is a novel and successful Multi-Objective Evolutionary Algorithms(MOEA) which utilizes the idea of problem decomposition to tackle the complexity from multiple obj...
Wudong Liu, Qingfu Zhang, Edward P. K. Tsang, Cao ...