نماذج المحاكاة- محاكاة مونتي كارلو- كأسلوب كمي من أساليب النمذجة واتخاذ القرارات - مقاربة نظرية وتطبيقية

2021 ◽  
Vol 1 (1) ◽  
Author(s):  
محمد الأمين ◽  
بن حامد عبد الغني ◽  
مراس محمد
Keyword(s):  
Monte Carlo Simulation ◽  
Monte Carlo ◽  
Quantitative Methods ◽  
Practical Importance ◽  
Investment Project ◽  
Simulation Method ◽  
Period Analysis ◽  
Investment Projects ◽  
Monte Carlo Simulation Model

Our research aims to try to present the modeling mechanisms in the field of simulation and quantitative methods. The research is a presentation of the role of quantitative methods in making investment project evaluation decisions, more than that and is the use of the Monte Carlo simulation model in evaluation and multi-period analysis of investment projects under conditions Risk and uncertainty. And highlighting the theoretical, scientific and practical importance of the Monte Carlo simulation method in particular, and the importance of using quantitative methods in helping to make decisions in general

The specificities of risk identification and express estimation of investment projects in modern conditions

2019 ◽  
pp. 69-86
Author(s):  
Liana Chechenova ◽  
Natalya Volykhina ◽  
Yuriy Egorov
Keyword(s):  
Monte Carlo Simulation ◽  
Monte Carlo ◽  
Risk Factor ◽  
Investment Project ◽  
Simulation Method ◽  
Modern Concept ◽  
Monte Carlo Simulation Method ◽  
Investment Projects ◽  
Study Results ◽  
Project Risks

Objective: When assessing the risks of an investment project, it is necessary to take into account the uniqueness of each project, which requires the search for completely new solutions, the application and combination of various tools and assessment methods for the effective implementation of the project. The objective is to develop and test an algorithm for express risk assessment of an investment project using an integral risk factor. In order to achieve this the following issues are considered: the development of the risk theory and the main stages of its development, the modern concept of risk and risk classification in the context of investment projects, modern methods for assessing the risks of investment projects and their problems. Next, the concept of an integral risk factor is introduced and an express assessment of risks of a local investment project is carried out using an integral risk factor. Methods: The classical methods of identifying and assessing project risks (the method of expert estimates, the Monte-Carlo simulation method), the comparative method, analysis, and synthesis are used in the study. Results: The basic characteristics of the concept of “risk” inherent in the modern understanding were formulated. A new concept of the integral risk factor and the method of its calculation were proposed. Alternative scenarios for the implementation of the investment project using the integral risk factor were developed. An algorithm for complex risk express assessment of an investment project on a multi-brand dealer auto center construction was developed by means of an integral risk factor and Monte-Carlo simulation method. Practical importance: The developed algorithm can be used by managers to identify and evaluate or carry out an express assessment of complex risks of investment projects in the process of operating real projects, as well as to provide background for developing new and more advanced methods of project risks assessment.

An investigation of the effect of gold nanoparticles with different concentrations on increasing absorbed dose: an empirical and simulation study

2018 ◽  
Vol 18 (02) ◽  
pp. 191-197
Author(s):  
Masoumeh Hoseinnezhad ◽  
Mohammad Mahdavi ◽  
Seyyed R. M. Mahdavi ◽  
Mobarake Mahdavizade
Keyword(s):  
Monte Carlo Simulation ◽  
Gold Nanoparticles ◽  
Monte Carlo ◽  
Absorbed Dose ◽  
Simulation Method ◽  
Dose Enhancement ◽  
Depth Dose ◽  
Optical Ct ◽  
Ct System ◽  
Monte Carlo Simulation Model

AbstractPurposeThe purpose of this study was to determine the dose enhancement factor (DEF) of gold nanoparticles in a dosimeter gel and construct percentage depth dose curves, using the Optical CT system and the Monte Carlo simulation model, to determine the effect of increasing the dose caused by increasing the concentration of gold nanoparticles at depths in the gel.Materials and methodsThe Magic-f Gel was made based on the relevant protocol in the physics lab. To determine the amount of the increase in the absorbed dose, the gold nanoparticles were added to the gel and irradiated. An increase in the dose after adding nanoparticles to the gel vials was estimated both with the Optical CT system and by the Monte Carlo simulation method.ResultsDose enhancement curves for doses of 2, 4 and 6 Gy were prepared for gel vials without adding nanoparticles, and nanoparticle gels at concentrations 0·17, 3 and 6 mM. Also, the DEF was estimated. For the 0·17 mM molar gel, the DEF for 2, 4 and 6 Gy was 0·7, 0·743 and 0·801, respectively. For the 3 mM gel, it was 1·98, 2·5 and 2·2, and for the 6 mM gel, it was 37·4, 4·24 and 4·71, respectively.ConclusionThe enhancement of the dose after adding gold nanoparticles was confirmed both by experimental data and by simulation data.

scholarly journals Economic Disposal Quantity of Leftovers kept in storage: a Monte Carlo simulation method

2019 ◽  
Vol 9 (1) ◽  
pp. 522-529
Author(s):  
R. Assis ◽  
P. Carmona Marques ◽  
J. Oliveira Santos ◽  
R. Vidal
Keyword(s):  
Monte Carlo Simulation ◽  
Monte Carlo ◽  
Cost Effective ◽  
Simulation Method ◽  
Minimum Length ◽  
Monte Carlo Simulation Method ◽  
Limit Time ◽  
Effective Decision ◽  
Effective Decision Making ◽  
Monte Carlo Simulation Model

AbstractThis article describes how to reach an item’s threshold, or in other words, the limit time for it to be retrieved from stock and sold for a different use, as well as the remaining foreseen period for this situation to occur. Once a minimum length, or weight, is reached, left quantities are more difficult to sell, as demand often exceeds the remaining parts or leftovers. The number of unfulfilled orders increases, as time goes by, until it becomes further cost effective to dispose the leftover and sell it for a lower price and alternative use. A Monte Carlo simulation model was built in order to consider the randomness of future transactions and quantifying consequences providing this way a simple and effective decision-making framework.

Decision Making Under Uncertainty in Pipeline Projects Using Monte Carlo Simulation

2004 ◽  
Author(s):  
Claudio de Brito Garcia ◽  
Leandro Bastos Machado
Keyword(s):  
Monte Carlo Simulation ◽  
Monte Carlo ◽  
Risk Analysis ◽  
Capital Investment ◽  
Net Present Value ◽  
Investment Project ◽  
Free Cash Flow ◽  
Investment Projects ◽  
Economical Analysis ◽  
Natural Gas Transmission

Uncertainty about a situation can often indicate risk, which is the possibility of loss, damage, or any other undesirable event. Most people and organization desire low or minimized risk, which would translate to stand to a scenario of high probability of success, profit, or some form of gain. This work shows the importance of risk analysis when it comes to compare two capital investment projects in the natural gas transmission business. A transmission company needs to choose between two alternatives for capacity expansion of a pipeline, with a maximum value for the transmission tariff previously agreed to the shipper. At first, the transmission tariff is calculated by the conventional method that comprises iterative calculation from an arbitrary value, until the project Net Present Value (NPV) reaches zero. Once calculated, the lower of the transmission tariffs associated to the two expansion projects indicates the best choice. That’s the way the majority of companies perform their economical analysis of the proposed problem. Monte Carlo Simulation risk analysis technique is a powerful tool to asses the risk associated to a capital investment project, which can be summarized as the probability of undesired results. The risk calculation is based on the uncertainties associated to the input data used to build the project free cash flow, and the simulation produces a frequency distribution, or histogram, for, the NPV of a project. As will be seen in the work, the investment with the largest expected NPV may not always be the best investment alternative.

scholarly journals Uncertainty Cost Functions in Climate-Dependent Controllable Loads in Commercial Environments

Energies ◽  
2021 ◽  
Vol 14 (10) ◽  
pp. 2885
Author(s):  
Daniel Losada ◽  
Ameena Al-Sumaiti ◽  
Sergio Rivera
Keyword(s):  
Monte Carlo Simulation ◽  
Monte Carlo ◽  
Simulation Method ◽  
Electricity Sector ◽  
Cost Functions ◽  
Density Estimator ◽  
Monte Carlo Simulation Method ◽  
Commercial Building ◽  
Complementary Method ◽  
The Cost

This article presents the development, simulation and validation of the uncertainty cost functions for a commercial building with climate-dependent controllable loads, located in Florida, USA. For its development, statistical data on the energy consumption of the building in 2016 were used, along with the deployment of kernel density estimator to characterize its probabilistic behavior. For validation of the uncertainty cost functions, the Monte-Carlo simulation method was used to make comparisons between the analytical results and the results obtained by the method. The cost functions found differential errors of less than 1%, compared to the Monte-Carlo simulation method. With this, there is an analytical approach to the uncertainty costs of the building that can be used in the development of optimal energy dispatches, as well as a complementary method for the probabilistic characterization of the stochastic behavior of agents in the electricity sector.

Sign in / Sign up

Export Citation Format

Share Document