Monte Carlo simulation is widely used to price complex nancial instruments. Recent theoretical results and extensive computer testing indicate that deterministic methods may be far superior in speed and conndence. Simulations using the Sobol or Faure points are examples of deterministic methods. For the sake of brevity, we refer to a deterministic method using the name of the sequence of points...

We have been developing Monte Carlo Techniques for calculating primary and scatter photon distributions in PET. Our first goal has been to accelerate the Monte Carlo Code for fast PET simulation. Our second goal has been to use the simulation to analyze scatter effects in PET and explore the potential for eventual use in scatter correction of clinical 3-D PET studies. We have reduced the execut...

A description of Monte Carlo methods for simulation of proteins is given. Advantages and disadvantages of the Monte Carlo approach are presented. The theoretical basis for calculating equilibrium properties of biological molecules by the Monte Carlo method is presented. Some of the standard and some of the more recent ways of performing Monte Carlo on proteins are presented. A discussion of the...

Monte Carlo analysis has become nearly ubiquitous since its introduction, now over 65 years ago. It is an important tool in many assessments of the reliability and robustness of systems, structures or solutions. As the deterministic core simulation can be lengthy, the computational costs of Monte Carlo can be a limiting factor. To reduce that computational expense as much as possible, sampling ...

In this paper we investigate an efficient implementation of the Monte Carlo EM algorithm based on Quasi-Monte Carlo sampling. The Monte Carlo EM algorithm is a stochastic version of the deterministic EM (Expectation-Maximization) algorithm in which an intractable E-step is replaced by a Monte Carlo approximation. Quasi-Monte Carlo methods produce deterministic sequences of points that can signi...

ntroduction:  monte  carlo  simulation  is  the  most  accurate  method  of  simulating  radiation  transport  and  predicting doses at different points of interest in radiotherapy. a great advantage of the monte carlo method  compared  to  the  deterministic  methods  is  the  ability  to  deal  accurately  with  any  complex  geometry.  its  disadvantage is the extremely long computing time r...

we compare two approaches for a markovian model in flexible manufacturing systems (fmss) using monte carlo simulation. the model which is a development of fazlollahtabar and saidi-mehrabad (2013), considers two features of automated flexible manufacturing systems equipped with automated guided vehicle (agv) namely, the reliability of machines and the reliability of agvs in a multiple agv jobsho...