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» Algorithmic randomness of continuous functions
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GECCO
2006
Springer
153views Optimization» more  GECCO 2006»
14 years 10 months ago
On the local performance of simulated annealing and the (1+1) evolutionary algorithm
Simulated annealing and the (1+1) EA, a simple evolutionary algorithm, are both general randomized search heuristics that optimize any objective function with probability
Thomas Jansen, Ingo Wegener
STACS
2010
Springer
15 years 1 months ago
Two-phase Algorithms for the Parametric Shortest Path Problem
Abstract. A parametric weighted graph is a graph whose edges are labeled with continuous real functions of a single common variable. For any instantiation of the variable, one obta...
Sourav Chakraborty, Eldar Fischer, Oded Lachish, R...
WSC
2008
14 years 9 months ago
Discrete stochastic optimization using linear interpolation
We consider discrete stochastic optimization problems where the objective function can only be estimated by a simulation oracle; the oracle is defined only at the discrete points....
Honggang Wang, Bruce W. Schmeiser
AUTOMATICA
2004
92views more  AUTOMATICA 2004»
14 years 6 months ago
Randomized algorithms for quadratic stability of quantized sampled-data systems,
In this paper, we present a novel development of randomized algorithms for quadratic stability analysis of sampled-data systems with memoryless quantizers. The speci
Hideaki Ishii, Tamer Basar, Roberto Tempo
VMV
2001
108views Visualization» more  VMV 2001»
14 years 8 months ago
A Theoretical Comparison of Monte Carlo Radiosity Algorithms
In this paper, we present a theoretical analysis of the error with three basic Monte Carlo radiosity algorithms, based on continuous collision shooting random walks, discrete coll...
Philippe Bekaert, Hans-Peter Seidel