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» Terminating Decision Algorithms Optimally
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CEC
2010
IEEE
15 years 3 months ago
Designing airfoils using a reference point based evolutionary many-objective particle swarm optimization algorithm
— In this paper, we illustrate the use of a reference point based many-objective particle swarm optimization algorithm to optimize low-speed airfoil aerodynamic designs. Our fram...
Upali K. Wickramasinghe, Robert Carrese, Xiaodong ...
GECCO
2007
Springer
137views Optimization» more  GECCO 2007»
15 years 9 months ago
Learning and anticipation in online dynamic optimization with evolutionary algorithms: the stochastic case
The focus of this paper is on how to design evolutionary algorithms (EAs) for solving stochastic dynamic optimization problems online, i.e. as time goes by. For a proper design, t...
Peter A. N. Bosman, Han La Poutré
GECCO
2007
Springer
155views Optimization» more  GECCO 2007»
15 years 9 months 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...
CEC
2007
IEEE
15 years 9 months ago
Light beam search based multi-objective optimization using evolutionary algorithms
Abstract— For the past decade or so, evolutionary multiobjective optimization (EMO) methodologies have earned wide popularity for solving complex practical optimization problems,...
Kalyanmoy Deb, Abhay Kumar
EMO
2006
Springer
173views Optimization» more  EMO 2006»
15 years 6 months ago
Differential Evolution versus Genetic Algorithms in Multiobjective Optimization
This paper presents a comprehensive comparison between the performance of state-of-the-art genetic algorithms NSGA-II, SPEA2 and IBEA and their differential evolution based variant...
Tea Tusar, Bogdan Filipic