Parallel Simulations of Manufacturing Processing using Simpy, a Python-Based Discrete Event Simulation Tool

2006 ◽  
Author(s):  
Victor Castillo
Keyword(s):  
Discrete Event Simulation ◽  
Discrete Event ◽  
Simulation Tool ◽  
Parallel Simulations ◽  
Event Simulation

Capacity Decision in Emergency Hospital Operation Rooms

2018 ◽  
pp. 140-155
Author(s):  
Ana Carolina Pereira de Vasconcelos Silva ◽  
Daniel Bouzon Nagem Assad ◽  
Thais Spiegel
Keyword(s):  
Emergency Department ◽  
Problem Solving ◽  
Discrete Event Simulation ◽  
Operations Management ◽  
Discrete Event ◽  
Design Management ◽  
Simulation Tool ◽  
Event Simulation ◽  
Production Distribution ◽  
Capacity Decision

The operations management is a multidisciplinary field that investigates, for instance, the design, management and processes improvement focused on the development, production, distribution and delivery of products and services, encompassing activities such as the implementation of policies, making quota decisions, identification and problem solving, response to uncertainty, among others. Regarding the resources dimensioning in hospitals, the Brazilian scenario is limited to legislative instruments that assume a prior and added sizing. This chapter uses a discrete event simulation tool to set the amount of operation rooms needed for patient care in an emergency department, so that emergency patients have guaranteed compliance, minimizing the cancellation of elective surgeries because of this type of demand. As a result, it was found that the minimum amount established by normative instruments was not appropriate to the specific requirements of the organization.

A discrete event simulation tool to support and predict hospital and clinic staffing

2016 ◽  
Vol 23 (2) ◽  
pp. 124-133 ◽  
Author(s):  
Christopher M DeRienzo ◽  
Ryan J Shaw ◽  
Phillip Meanor ◽  
Emily Lada ◽  
Jeffrey Ferranti ◽  
...  
Keyword(s):  
Intensive Care Unit ◽  
Intensive Care ◽  
Neonatal Intensive Care Unit ◽  
Discrete Event Simulation ◽  
Neonatal Intensive Care ◽  
Discrete Event ◽  
Simulation Tool ◽  
Event Simulation ◽  
Discrete Event Simulation Model ◽  
Staffing Needs

We demonstrate how to develop a simulation tool to help healthcare managers and administrators predict and plan for staffing needs in a hospital neonatal intensive care unit using administrative data. We developed a discrete event simulation model of nursing staff needed in a neonatal intensive care unit and then validated the model against historical data. The process flow was translated into a discrete event simulation model. Results demonstrated that the model can be used to give a respectable estimate of annual admissions, transfers, and deaths based upon two different staffing levels. The discrete event simulation tool model can provide healthcare managers and administrators with (1) a valid method of modeling patient mix, patient acuity, staffing needs, and costs in the present state and (2) a forecast of how changes in a unit’s staffing, referral patterns, or patient mix would affect a unit in a future state.

scholarly journals Application potential of Agent Based Simulation and Discrete Event Simulation in Enterprise integration modelling concepts

2013 ◽  
Vol 1 (1) ◽  
pp. 33-42
Author(s):  
Pawel Pawlewski ◽  
Paulina Golinska ◽  
Paul-Eric Dossou
Keyword(s):  
Discrete Event Simulation ◽  
Selection Process ◽  
Discrete Event ◽  
Simulation Tool ◽  
Tool Selection ◽  
Enterprise Integration ◽  
Agent Based Simulation ◽  
Agent Based ◽  
Event Simulation ◽  
Application Potential

This paper aims to present the dilemma of simulation tool selection. Authors discuss the examples of methodologies of enterprises architectures (CIMOSA and GRAI) where agent approach is used to solve planning and managing problems. Actually simulation is widely used and practically only one tool which can enable verification of complex systems. Many companies face the problem, which simulation tool is appropriate to use for verification. Selected tools based on ABS and DES are presented. Some tools combining DES and ABS approaches are described. Authors give some recommendation on selection process.

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