Monte Carlo simulation applied to support risk-based decision making in electricity distribution networks

2015 ◽  
Author(s):  
Shiromani A.V. Goerdin ◽  
Johan J. Smit ◽  
Ravish P.Y. Mehairjan
Keyword(s):  
Decision Making ◽  
Monte Carlo Simulation ◽  
Monte Carlo ◽  
Distribution Networks ◽  
Electricity Distribution

A study on appropriate investment of pipeline rehabilitation for water distribution network

2005 ◽  
Vol 5 (2) ◽  
pp. 31-38
Author(s):  
A. Asakura ◽  
A. Koizumi ◽  
O. Odanagi ◽  
H. Watanabe ◽  
T. Inakazu
Keyword(s):  
Monte Carlo Simulation ◽  
Monte Carlo ◽  
Water Supply ◽  
Water Distribution ◽  
Ad Hoc ◽  
Distribution Network ◽  
Water Distribution Network ◽  
Distribution Networks ◽  
Optimal Basis ◽  
Model Case

In Japan most of the water distribution networks were constructed during the 1960s to 1970s. Since these pipelines were used for a long period, pipeline rehabilitation is necessary to maintain water supply. Although investment for pipeline rehabilitation has to be planned in terms of cost-effectiveness, no standard method has been established because pipelines were replaced on emergency and ad hoc basis in the past. In this paper, a method to determine the maintenance of the water supply on an optimal basis with a fixed budget for a water distribution network is proposed. Firstly, a method to quantify the benefits of pipeline rehabilitation is examined. Secondly, two models using Integer Programming and Monte Carlo simulation to maximize the benefits of pipeline rehabilitation with limited budget were considered, and they are applied to a model case and a case study. Based on these studies, it is concluded that the Monte Carlo simulation model to calculate the appropriate investment for the pipeline rehabilitation planning is both convenient and practical.

scholarly journals Sales forecasting in a mechanical component manufacturer: comparison between monte carlo simulation and time series analysis

2019 ◽  
Vol 10 (4) ◽  
pp. 1324
Author(s):  
Kevin William Matos Paixão ◽  
Adriano Maniçoba da Silva
Keyword(s):  
Decision Making ◽  
Time Series ◽  
Monte Carlo Simulation ◽  
Monte Carlo ◽  
Moving Average ◽  
Prediction Methods ◽  
Future Scenario ◽  
Sales Forecast ◽  
Forecasting Methods ◽  
Weighted Moving Average

Organizations today are required to be prepared for future situations. This preparation can generate a significant competitive advantage. In order to maximize benefits, several companies are investing more in techniques that simulate a future scenario and enable more precise and assertive decision making. Among these techniques are the sales forecasting methods. The comparison between the known techniques is an important factor to increase the assertiveness of the forecast. The objective of this study was to compare the sales forecast results of a mechanical components manufacturing company obtained through five different techniques, divided into two groups, the first one, which uses the fundamentals of the time series, and the second one is the Monte Carlo simulation. The following prediction methods were compared: moving average, weighted moving average, least squares, holt winter and Monte Carlo simulation. The results indicated that the methods that obtained the best performance were the moving average and the weighted moving average attaining 94% accuracy.

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