In this paper, the authors compare a Monte Carlo method and an optimization-based approach using genetic algorithms for sequentially generating space-filling experimental designs. It is shown that Monte Carlo methods perform better than genetic algorithms for this specific problem.

Kinetic Monte Carlo simulation was applied to investigation of kinetics and mechanism of oxalic acid degradation by direct and heterogeneous catalytic ozonation. La-containing perovskites including LaFeO3, LaNiO3, LaCoO3 and LaMnO3 was studied as catalyst for oxalic acid ozonation. The reaction kinetic mechanisms of each abovementioned catalytic systems has been achieved. The rate constants val...

By analogy with Monte Carlo algorithms, we propose new strategies for design and redesign of small molecule libraries in high-throughput experimentation, or combinatorial chemistry. Several Monte Carlo methods are examined, including Metropolis, three types of biased schemes, and composite moves that include swapping or parallel tempering. Among them, the biased Monte Carlo schemes exhibit part...

We present a new methodology, based on a combination of genetic algorithms and image morphometry, for matching the outcome of a Monte Carlo simulation to experimental observations of a far-from-equilibrium nanosystem. The Monte Carlo model used simulates a colloidal solution of nanoparticles drying on a solid substrate and has previously been shown to produce patterns very similar to those obse...

In this paper, we deal with the pricing of power options when the dynamics of the risky underling asset follows the double stochastic volatility with double jump model. We prove efficiency of our considered model by fast Fourier transform method, Monte Carlo simulation and numerical results using power call options i.e. Monte Carlo simulation and numerical results show that the fast Fourier tra...

monte carlo simulation is a standard technique for project risk analysis. however, some assumptions of this technique are not reasonable in real world. when a project falls behind the schedule, managers take actions to improve the performance. nevertheless, most of the simulation models as monte carlo omit these reactions in their analysis, which results in unreasonable wide distributions or ev...

Background: Inclusion of inhomogeneity corrections in intensity modulated small fields always makes conformal irradiation of lung tumor very complicated in accurate dose delivery.Objective: In the present study, the performance of five algorithms via Monte Carlo, Pencil Beam, Convolution, Fast Superposition and Superposition were evaluated in lung cancer Intensity Modulated Radiotherapy plannin...

In the last years, a remarkable research effort has been made in the area of wireless sensor networks. One of the main advantages of this kind of distributed system is the ability to determine the position of its nodes and the events sensed. Therefore, a simulation framework is required to compare the different location algorithms that could be used in a certain environment, in order to decide ...

Monte Carlo simulation is one of the main applications involving the use of random number generators. It is also one of the best methods of testing the randomness properties of such generators, by comparing results of simulations using different generators with each other, or with analytic results. Here we compare the performance of some popular random number generators by high precision Monte ...

the determination of gyration radius is a strong research for configuration of a macromolecule. italso reflects molecular compactness shape. in this work, to characterize the behavior of theprotein, we observe quantities such as the radius of gyration and the average energy. we studiedthe changes of these factors as a function of temperature for acetylcholine receptor protein in gasphase with n...