scholarly journals Biopolymer structure simulation and optimization via fragment regrowth Monte Carlo

2007 ◽  
Vol 126 (22) ◽  
pp. 225101 ◽  
Author(s):  
Jinfeng Zhang ◽  
S. C. Kou ◽  
Jun S. Liu
Keyword(s):  
Monte Carlo ◽  
Simulation And Optimization ◽  
Structure Simulation ◽  
Biopolymer Structure

scholarly journals FRESS: an Efficient Monte Carlo Method for Biopolymer Structure Simulation

2009 ◽  
Vol 96 (3) ◽  
pp. 653a
Author(s):  
Jinfeng Zhang ◽  
Yue Li ◽  
Sam C. Kou ◽  
Gary Tyson ◽  
Jun S. Liu
Keyword(s):  
Monte Carlo ◽  
Monte Carlo Method ◽  
Structure Simulation ◽  
Biopolymer Structure

Monte carlo simulation and optimization of three-axis neutron spectrometer for the PIK reactor

2007 ◽  
Vol 52 (3) ◽  
pp. 552-557
Author(s):  
R. G. Burkovskiĭ ◽  
S. B. Vakhrushev ◽  
O. I. Zvorykina ◽  
A. A. Naberezhnov ◽  
N. M. Okuneva ◽  
...  
Keyword(s):  
Monte Carlo Simulation ◽  
Monte Carlo ◽  
Neutron Spectrometer ◽  
Simulation And Optimization

A Simple Reverse Monte Carlo Algorithm for Structure Simulation of Multi-Component Amorphous Solids

1997 ◽  
Vol 11 (24) ◽  
pp. 1047-1055 ◽  
Author(s):  
M. Andrecut
Keyword(s):  
Monte Carlo ◽  
Monte Carlo Method ◽  
Amorphous Solids ◽  
Monte Carlo Algorithm ◽  
Reverse Monte Carlo ◽  
Structure Simulation ◽  
Reverse Monte Carlo Method

A simple Reverse Monte Carlo algorithm for structure simulations of multi-component amorphous solids is presented. The described algorithm is based on the standard reverse Monte Carlo method,1,2 developed for the monoatomic case, the application for poliatomic case being assured by using the Warren–Krutter–Morningstar approximation.3 An application for metal-metalloid glasses is also presented.

scholarly journals Inventory simulation model of frozen-meat for food-safety program

2018 ◽  
Vol 3 (1) ◽  
pp. 36-43
Author(s):  
Moch Yandra Darajat ◽  
Komarudin Komarudin ◽  
Akhmad Hidayatno
Keyword(s):  
Monte Carlo Simulation ◽  
Monte Carlo ◽  
Food Safety ◽  
Optimization Model ◽  
Moving Average ◽  
Fresh Meat ◽  
Inventory Policy ◽  
Safety Program ◽  
Simulation And Optimization ◽  
The Cost

This research discusses the application of inventory simulation and optimization model for food safety program in Indonesia. Frozen meat is a complementary commodity for fresh meat that has an inadequate supply in the country. The disadvantage of frozen meat is that it needs to be stored in a refrigerator to maintain its quality and thus increases the cost. Therefore, an appropriate inventory policy is crucial to minimize the cost. In order to deal with this situation, a Monte Carlo simulation followed by an optimization model is proposed. Specifically, the Moving Average and the Winter Methods are used to predict the demand in the future. The results show the best inventory policy thus the cost is minimized and the national needs are satisfied.

Modeling, simulation and optimization of maintenance cost aspects on multi-unit systems by stochastic Petri nets with predicates

SIMULATION ◽  
2018 ◽  
Vol 95 (5) ◽  
pp. 461-478 ◽  
Author(s):  
Fernando P Santos ◽  
Ângelo P Teixeira ◽  
C. Guedes Soares
Keyword(s):  
Monte Carlo Simulation ◽  
Monte Carlo ◽  
Petri Nets ◽  
Stochastic Petri Nets ◽  
Maintenance Cost ◽  
Maintenance Strategies ◽  
Simulation And Optimization ◽  
System Components ◽  
Parallel Configuration ◽  
Analytical Approaches

The paper addresses repairable multi-unit systems with a series–parallel configuration for which maintenance strategies are modeled by generalized stochastic Petri nets (GSPN) with predicates coupled with Monte Carlo simulation. Four maintenance strategies consisting of basic periodic preventive and corrective maintenance, and both combined with opportunistic maintenance (OM) strategies, are considered. Failure and repair distributions of the system components are independent, and repairs are considered to be perfect. Times to failure of degraded components follow a Weibull distribution with increasing failure rate over time. The maintenance strategies are optimized so as to minimize the total maintenance costs of the system while maximizing availability. A comparison is drawn between OM and non-OM. The aim is to show that GSPN with predicates, in combination with Monte Carlo simulation, is a powerful, flexible, efficient, and intuitive approach for modeling and optimizing practical maintenance strategies on multi-unit complex systems, modeling the dynamic behavior resulting from the interaction between system components and economic dependencies. The merits and advantages of GSPN coupled with Monte Carlo simulation are enhanced relative to other, analytical, approaches.

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