Implementing a discrete-event simulation software selection methodology for supporting decision making at Accenture

2010 ◽  
Vol 61 (10) ◽  
pp. 1446-1458 ◽  
Author(s):  
T W Tewoldeberhan ◽  
A Verbraeck ◽  
V Hlupic
Keyword(s):  
Decision Making ◽  
Discrete Event Simulation ◽  
Discrete Event ◽  
Simulation Software ◽  
Software Selection ◽  
Event Simulation ◽  
Selection Methodology

Discrete Event Simulation Of The COVID-19 Sample Collection Point Operation

2021 ◽  
Author(s):  
Martina Kuncova ◽  
Katerina Svitkova ◽  
Alena Vackova ◽  
Milena Vankova
Keyword(s):  
Discrete Event Simulation ◽  
Waiting Times ◽  
Discrete Event ◽  
Real Data ◽  
Simulation Software ◽  
Sample Collection ◽  
The Real ◽  
Event Simulation ◽  
Collection Process ◽  
Collection Point

The year 2020 was very challenging for everyone due to the COVID-19 pandemic. Many people turn their lives upside down from day to day. Politicians had to impose completely unprecedented measures, and doctors immediately had to adapt to the huge influx of patients and the massive demand for testing. Of course, not all processes could be planned completely efficiently, given that the situation literally changes from minute to minute, but sometimes better planning could improve the real processes. This contribution deals with the application of simulation software SIMUL8 to the analysis of the COVID-19 sample collection process in a drive-in point in a hospital. The main aim is to create a model based on the real data and then to find out the suitable number of other staff (medics) helping a doctor during the process to decrease the number of unattended patients and their waiting times.

scholarly journals Optimization of tillage and sowing operations using discrete event simulation 

2018 ◽  
Vol 64 (No. 4) ◽  
pp. 187-194 ◽  
Author(s):  
Armaghan Kosari Moghaddam ◽  
Hassan Sadrnia ◽  
Hassan Aghel ◽  
Mohammad Bannayan
Keyword(s):  
Discrete Event Simulation ◽  
Discrete Event ◽  
Daily Basis ◽  
Simulation Software ◽  
Field Size ◽  
Daily Work ◽  
Event Simulation ◽  
Significant Difference ◽  
Average Work ◽  
Work Method

A simulation model was developed for secondary tillage and sowing operations in autumn, using discrete event simulation technique in Arena<sup>®</sup> simulation software (Version 14). Eight machinery sets were evaluated on a 50-hectare farm. Total costs including fixed-costs, variable costs and timeliness costs were calculated for each machinery set. Timeliness costs were estimated for 21-years period on daily basis (Daily Work method) and compared with another method (Average Work method) based on the equation proposed by ASAE Standards, EP 496.3FEB2006. The Inputs of the model were machinery sets, field size, machines performances and daily soil workability state. The optimization criteria were the lowest costs and lowest standard deviation in daily work method plus the lowest costs based on average work method. The validity of the model was evaluated by comparing the output of the model with field observed data collected from various farms. Results revealed that there was no significant difference (P &gt; 0.01) between the observed and predicted finish day. 

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