A new importance sampling Monte Carlo method for a flow network reliability problem

2002 ◽  
Vol 49 (2) ◽  
pp. 204-228 ◽  
Author(s):  
St�phane Bulteau ◽  
Mohamed El Khadiri
Keyword(s):  
Monte Carlo ◽  
Monte Carlo Method ◽  
Importance Sampling ◽  
Network Reliability ◽  
Flow Network ◽  
Reliability Problem

PERMUTATIONAL METHODS FOR PERFORMANCE ANALYSIS OF STOCHASTIC FLOW NETWORKS

2013 ◽  
Vol 28 (1) ◽  
pp. 21-38 ◽  
Author(s):  
Ilya Gertsbakh ◽  
Reuven Rubinstein ◽  
Yoseph Shpungin ◽  
Radislav Vaisman
Keyword(s):  
Monte Carlo ◽  
Monte Carlo Method ◽  
Performance Analysis ◽  
Failure Probability ◽  
Stochastic Flow ◽  
Maximal Flow ◽  
Convergence Properties ◽  
Flow Networks ◽  
Flow Network ◽  
Random Failures

In this paper we show how the permutation Monte Carlo method, originally developed for reliability networks, can be successfully adapted for stochastic flow networks, and in particular for estimation of the probability that the maximal flow in such a network is above some fixed level, called the threshold. A stochastic flow network is defined as one, where the edges are subject to random failures. A failed edge is assumed to be erased (broken) and, thus, not able to deliver any flow. We consider two models; one where the edges fail with the same failure probability and another where they fail with different failure probabilities. For each model we construct a different algorithm for estimation of the desired probability; in the former case it is based on the well known notion of the D-spectrum and in the later one—on the permutational Monte Carlo. We discuss the convergence properties of our estimators and present supportive numerical results.

scholarly journals Exact ground state Monte Carlo method for Bosons without importance sampling

2009 ◽  
Vol 131 (15) ◽  
pp. 154108 ◽  
Author(s):  
M. Rossi ◽  
M. Nava ◽  
L. Reatto ◽  
D. E. Galli
Keyword(s):  
Monte Carlo ◽  
Monte Carlo Method ◽  
Importance Sampling ◽  
Ground State ◽  
Exact Ground State

IMPORTANCE-SAMPLING MONTE CARLO METHOD AND ENTROPY OF q-STATE POTTS MODEL

1992 ◽  
Vol 06 (18) ◽  
pp. 1121-1129
Author(s):  
HSING-MEI HUANG
Keyword(s):  
Phase Transition ◽  
Monte Carlo ◽  
Monte Carlo Method ◽  
Importance Sampling ◽  
Potts Model ◽  
Continuous Phase ◽  
Entropy Function ◽  
Two Dimensional ◽  
Potts Models ◽  
Continuous Phase Transition

An importance-sampling Monte Carlo method is applied to the calculation of Γ(E), the number of states for a given energy E, and Γ(E, S), the number of states for given energy E and spin S, of antiferromagnetic two-dimensional q=2,3,4,5,6 Potts models. The entropy function is derived for various temperatures, and our results for the q=3 model show a continuous phase transition.

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