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ICAI
2003
13 years 6 months ago
Exploiting the Marginal Profits of Constraints with Evolutionary Multi-Objective Optimization Techniques
Many real-world search and optimization problems naturally involve constraint handling. Recently, quite a few heuristic methods were proposed to solve the nonlinear constrained op...
Zhenyu Yan, Wei Zhi, Lishan Kang
CEC
2007
IEEE
13 years 11 months ago
SAT-decoding in evolutionary algorithms for discrete constrained optimization problems
— For complex optimization problems, several population-based heuristics like Multi-Objective Evolutionary Algorithms have been developed. These algorithms are aiming to deliver ...
Martin Lukasiewycz, Michael Glaß, Christian ...
EUSFLAT
2009
156views Fuzzy Logic» more  EUSFLAT 2009»
13 years 2 months ago
Interactive Fuzzy Modeling by Evolutionary Multiobjective Optimization with User Preference
One of the new trends in genetic fuzzy systems (GFS) is the use of evolutionary multiobjective optimization (EMO) algorithms. This is because EMO algorithms can easily handle two c...
Yusuke Nojima, Hisao Ishibuchi
PPSN
1998
Springer
13 years 9 months ago
A Decoder-Based Evolutionary Algorithm for Constrained Parameter Optimization Problems
Several methods have been proposed for handling nonlinear constraints by evolutionary algorithms for numerical optimization problems; a survey paper [7] provides an overview of var...
Slawomir Koziel, Zbigniew Michalewicz