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» Randomness, Stochasticity and Approximations
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MP
2006
90views more  MP 2006»
13 years 7 months ago
Solving multistage asset investment problems by the sample average approximation method
The vast size of real world stochastic programming instances requires sampling to make them practically solvable. In this paper we extend the understanding of how sampling affects ...
Jörgen Blomvall, Alexander Shapiro
MOR
2007
149views more  MOR 2007»
13 years 7 months ago
LP Rounding Approximation Algorithms for Stochastic Network Design
Real-world networks often need to be designed under uncertainty, with only partial information and predictions of demand available at the outset of the design process. The field ...
Anupam Gupta, R. Ravi, Amitabh Sinha
SIAMMAX
2010
111views more  SIAMMAX 2010»
13 years 2 months ago
Stochastic Galerkin Matrices
We investigate the structural, spectral, and sparsity properties of Stochastic Galerkin matrices as they arise in the discretization of linear differential equations with random co...
Oliver G. Ernst, Elisabeth Ullmann
ACG
2006
Springer
14 years 1 months ago
RSPSA: Enhanced Parameter Optimization in Games
Most game programs have a large number of parameters that are crucial for their performance. Tuning these parameters by hand is rather difficult. Therefore automatic optimization a...
Levente Kocsis, Csaba Szepesvári, Mark H. M...
ISCAS
2005
IEEE
133views Hardware» more  ISCAS 2005»
14 years 1 months ago
Multiobjective VLSI cell placement using distributed simulated evolution algorithm
— Simulated Evolution (SimE) is a sound stochastic approximation algorithm based on the principles of adaptation. If properly engineered it is possible for SimE to reach nearopti...
Sadiq M. Sait, Ali Mustafa Zaidi, Mustafa I. Ali