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ENC
2003
IEEE
15 years 3 months ago
Multiobjective-Based Concepts to Handle Constraints in Evolutionary Algorithms
This paper presents the main multiobjective optimization concepts that have been used in evolutionary algorithms to handle constraints in global optimization problems. A review of...
Efrén Mezura-Montes, Carlos A. Coello Coell...
CEC
2009
IEEE
15 years 4 months ago
Evolving modular neural-networks through exaptation
— Despite their success as optimization methods, evolutionary algorithms face many difficulties to design artifacts with complex structures. According to paleontologists, living...
Jean-Baptiste Mouret, Stéphane Doncieux
88
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PPSN
2004
Springer
15 years 3 months ago
SPEA2+: Improving the Performance of the Strength Pareto Evolutionary Algorithm 2
Multi-objective optimization methods are essential to resolve real-world problems as most involve several types of objects. Several multi-objective genetic algorithms have been pro...
Mifa Kim, Tomoyuki Hiroyasu, Mitsunori Miki, Shiny...
GECCO
2006
Springer
124views Optimization» more  GECCO 2006»
15 years 1 months ago
Rotated test problems for assessing the performance of multi-objective optimization algorithms
This paper presents four rotatable multi-objective test problems that are designed for testing EMO (Evolutionary Multiobjective Optimization) algorithms on their ability in dealin...
Antony W. Iorio, Xiaodong Li
GECCO
2008
Springer
363views Optimization» more  GECCO 2008»
14 years 11 months ago
Towards high speed multiobjective evolutionary optimizers
One of the major difficulties when applying Multiobjective Evolutionary Algorithms (MOEA) to real world problems is the large number of objective function evaluations. Approximate...
A. K. M. Khaled Ahsan Talukder