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» Performance modeling using Monte Carlo simulation
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WSC
2008
15 years 2 months ago
A particle filtering framework for randomized optimization algorithms
We propose a framework for optimization problems based on particle filtering (also called Sequential Monte Carlo method). This framework unifies and provides new insight into rand...
Enlu Zhou, Michael C. Fu, Steven I. Marcus
WSC
1998
15 years 1 months ago
Efficiency Improvement by Lattice Rules for Pricing Asian Options
This paper compares Monte Carlo methods, lattice rules, and other low-discrepancy point sets on the problem of evaluating asian options. The combination of these methods with vari...
Christiane Lemieux, Pierre L'Ecuyer
WSC
2000
15 years 1 months ago
Generating "dependent" quasi-random numbers
Under certain conditions on the integrand, quasi-Monte Carlo methods for estimating integrals (expectations) converge faster asymptotically than Monte Carlo methods. Motivated by ...
Shane G. Henderson, Belinda A. Chiera, Roger M. Co...
WSC
1998
15 years 1 months ago
Stopping Criterion for a Simulation-Based Optimization Method
We consider a new simulation-based optimization method called the Nested Partitions (NP) method. This method generates a Markov chain and solving the optimization problem is equiv...
Sigurdur Ólafsson, Leyuan Shi
ICPP
2007
IEEE
15 years 6 months ago
Parallel Algorithms for Bayesian Indoor Positioning Systems
We present two parallel algorithms and their Unified Parallel C implementations for Bayesian indoor positioning systems. Our approaches are founded on Markov Chain Monte Carlo si...
Konstantinos Kleisouris, Richard P. Martin