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ICTAI
2009
IEEE
13 years 4 months ago
A Confidence-Based Dominance Operator in Evolutionary Algorithms for Noisy Multiobjective Optimization Problems
This paper describes a noise-aware dominance operator for evolutionary algorithms to solve the multiobjective optimization problems (MOPs) that contain noise in their objective fu...
Pruet Boonma, Junichi Suzuki
GECCO
2010
Springer
227views Optimization» more  GECCO 2010»
13 years 9 months ago
Benchmarking SPSA on BBOB-2010 noisy function testbed
This paper presents the result for Simultaneous Perturbation Stochastic Approximation (SPSA) on the BBOB 2010 noisy testbed. SPSA is a stochastic gradient approximation strategy w...
Steffen Finck, Hans-Georg Beyer
GECCO
2010
Springer
188views Optimization» more  GECCO 2010»
13 years 9 months ago
Benchmarking real-coded genetic algorithm on noisy black-box optimization testbed
Originally, genetic algorithms were developed based on the binary representation of candidate solutions in which each conjectured solution is a fixed-length string of binary numb...
Thanh-Do Tran, Gang-Gyoo Jin
EMO
2005
Springer
68views Optimization» more  EMO 2005»
13 years 12 months ago
Multi-objective Optimization of Problems with Epistemic Uncertainty
Abstract. Multi-objective evolutionary algorithms (MOEAs) have proven to be a powerful tool for global optimization purposes of deterministic problem functions. Yet, in many real-w...
Philipp Limbourg
GPEM
2006
127views more  GPEM 2006»
13 years 6 months ago
A hierarchical particle swarm optimizer for noisy and dynamic environments
New Particle Swarm Optimization (PSO) methods for dynamic and noisy function optimization are studied in this paper. The new methods are based on the hierarchical PSO (H-PSO) and a...
Stefan Janson, Martin Middendorf