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» On the Brittleness of Evolutionary Algorithms
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ICASSP
2011
IEEE
14 years 1 months ago
A variable step size evolutionary affine projection algorithm
It is well known that the affine projection algorithm (APA) offers a good tradeoff between convergence rate/tracking and computational complexity. Recently, the evolutionary APA (...
Felix Albu, Constantin Paleologu, Jacob Benesty
CEC
2009
IEEE
15 years 4 months ago
An orthogonal multi-objective evolutionary algorithm with lower-dimensional crossover
Abstract— This paper proposes an multi-objective evolutionary algorithm. The algorithm is based on OMOEA-II[2]. A new linear breeding operator with lower-dimensional crossover an...
Song Gao, Sanyou Y. Zeng, Bo Xiao, Lei Zhang, Yulo...
EC
2000
96views ECommerce» more  EC 2000»
14 years 10 months ago
Multiobjective Evolutionary Algorithms: Analyzing the State-of-the-Art
Solving optimization problems with multiple (often conflicting) objectives is, generally, a very difficult goal. Evolutionary algorithms (EAs) were initially extended and applied ...
David A. van Veldhuizen, Gary B. Lamont
GECCO
2010
Springer
189views Optimization» more  GECCO 2010»
14 years 7 months ago
Multiobjective evolutionary algorithm for software project portfolio optimization
Large software companies have to plan their project portfolio to maximize potential portfolio return and strategic alignment, while balancing various preferences, and considering ...
Thomas Kremmel, Jirí Kubalík, Stefan...
GECCO
2008
Springer
186views Optimization» more  GECCO 2008»
14 years 11 months ago
A pareto following variation operator for fast-converging multiobjective evolutionary algorithms
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, Michael Kirley, Ra...