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GECCO
2007
Springer
184views Optimization» more  GECCO 2007»
14 years 2 months ago
Experimental analysis of binary differential evolution in dynamic environments
Many real-world optimization problems are dynamic in nature. The interest in the Evolutionary Algorithms (EAs) community in applying EA variants to dynamic optimization problems h...
Alp Emre Kanlikilicer, Ali Keles, Sima Uyar
EVOW
2006
Springer
13 years 12 months ago
A Preliminary Study on Handling Uncertainty in Indicator-Based Multiobjective Optimization
Abstract. Real-world optimization problems are often subject to uncertainties, which can arise regarding stochastic model parameters, objective functions and decision variables. Th...
Matthieu Basseur, Eckart Zitzler
ICML
1998
IEEE
14 years 9 months ago
Q2: Memory-Based Active Learning for Optimizing Noisy Continuous Functions
This paper introduces a new algorithm, Q2, foroptimizingthe expected output ofamultiinput noisy continuous function. Q2 is designed to need only a few experiments, it avoids stron...
Andrew W. Moore, Jeff G. Schneider, Justin A. Boya...
CEC
2009
IEEE
14 years 3 months ago
Enhancing MOEA/D with guided mutation and priority update for multi-objective optimization
—Multi-objective optimization is an essential and challenging topic in the domains of engineering and computation because real-world problems usually include several conflicting...
Chih-Ming Chen, Ying-Ping Chen, Qingfu Zhang
GECCO
2007
Springer
256views Optimization» more  GECCO 2007»
14 years 2 months ago
A particle swarm optimization approach for estimating parameter confidence regions
Point estimates of the parameters in real world models convey valuable information about the actual system. However, parameter comparisons and/or statistical inference requires de...
Praveen Koduru, Stephen Welch, Sanjoy Das