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» Sensitivity of trust-region algorithms to their parameters
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4OR
2005
51views more  4OR 2005»
13 years 5 months ago
Sensitivity of trust-region algorithms to their parameters
Abstract In this paper, we examine the sensitivity of trust-region algorithms on the parameters related to the step acceptance and update of the trust region. We show, in the conte...
Nicholas I. M. Gould, Dominique Orban, Annick Sart...
WSC
2007
13 years 7 months ago
Stochastic trust region gradient-free method (strong): a new response-surface-based algorithm in simulation optimization
Response Surface Methodology (RSM) is a metamodelbased optimization method. Its strategy is to explore small subregions of the parameter space in succession instead of attempting ...
Kuo-Hao Chang, L. Jeff Hong, Hong Wan
GECCO
2010
Springer
180views Optimization» more  GECCO 2010»
13 years 9 months ago
Comparison of NEWUOA with different numbers of interpolation points on the BBOB noisy testbed
In this paper, we study the performances of the NEW Unconstrained Optimization Algorithm (NEWUOA) with different numbers of interpolation points. NEWUOA is a trust region method, ...
Raymond Ros
NETWORKING
2000
13 years 6 months ago
Sensitivity of ABR Congestion Control Algorithms to Hurst Parameter Estimates
Optimal linear predictors can be utilised in ABR control algorithms for the management of self-similar network traffic. However, estimates of the Hurst parameter are required to ge...
Sven A. M. Östring, Harsha Sirisena, Irene Hu...
SEMCCO
2010
13 years 3 months ago
Differential Evolution Algorithm with Ensemble of Parameters and Mutation and Crossover Strategies
Differential Evolution (DE) has attracted much attention recently as an effective approach for solving numerical optimization problems. However, the performance of DE is sensitive ...
Rammohan Mallipeddi, Ponnuthurai Nagaratnam Sugant...