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» On the Brittleness of Evolutionary Algorithms
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CEC
2010
IEEE
14 years 10 months ago
Parallel hybrid evolutionary algorithms on GPU
Abstract— Over the last years, interest in hybrid metaheuristics has risen considerably in the field of optimization. Combinations of methods such as evolutionary algorithms and...
Thé Van Luong, Nouredine Melab, El-Ghazali ...
EMO
2001
Springer
209views Optimization» more  EMO 2001»
15 years 2 months ago
Comparison of Evolutionary and Deterministic Multiobjective Algorithms for Dose Optimization in Brachytherapy
We compare two multiobjective evolutionary algorithms, with deterministic gradient based optimization methods for the dose optimization problem in high-dose rate (HDR) brachythera...
Natasa Milickovic, Michael Lahanas, Dimos Baltas, ...
CEC
2008
IEEE
15 years 4 months ago
New evaluation criteria for the convergence of continuous evolutionary algorithms
—The first hitting time (FHT) plays an important role in convergence evaluation for evolutionary algorithms. However, the current criteria of the FHT are mostly under a hypothesi...
Ying Lin, Jian Huang, Jun Zhang
CEC
2005
IEEE
15 years 3 months ago
Designing comminution circuits with a multi-objective evolutionary algorithm
Mining is an important industry in Australia, contributing billions of dollars to the economy. The performance of a processing plant has a large impact on the profitability of a m...
Simon Huband, Luigi Barone, Philip Hingston, R. Ly...
GECCO
2005
Springer
109views Optimization» more  GECCO 2005»
15 years 3 months ago
A hybrid evolutionary algorithm for the p-median problem
A hybrid evolutionary algorithm (EA) for the p-median problem consist of two stages, each of which is a steady-state hybrid EA. These EAs encode selections of medians as subsets o...
István Borgulya