scholarly journals Discrete-Event Simulation of the Establishment of a Bare Beachhead for Long-Term Joint Logistics over the Shore (JLOTS) Operations

2017 ◽  
Vol 5 (2) ◽  
pp. 123-128
Author(s):  
Marqus Burrell ◽  
Jeffrey Demarest ◽  
Sarah LaRue ◽  
Angelo Martinez ◽  
Wilson Meyer
Keyword(s):  
Discrete Event Simulation ◽  
Discrete Event ◽  
The United States ◽  
Operational Conditions ◽  
Freedom Of Movement ◽  
Event Simulation ◽  
Early Entry ◽  
Sea Transportation ◽  
Development Center

The United States military uses Joint Logistics Over-the-Shore (JLOTS) operations to move soldiers, vehicles, and equipment across the globe for military and humanitarian missions. These logistics operations can only be accomplished through cooperation between commanders in all services.  The U.S. Army Engineer Research and Development Center is developing a tool to analyze a set of early entry alternatives to optimize mission effectives and efficiencies in order to facilitate assured mobility and freedom of movement. This program is currently being developed under the name Planning Logistics Analysis Network System (PLANS). PLANS comprehensively covers air, land, and sea transportation infrastructure, regions of avoidance, and more. This research addresses a gap in strategic and operational planning by modeling the establishment of JLOTS operations on bare beach environments. The West Point developed discrete event simulation will determine the amount of time it takes to prepare a beach to sustain JLOTS operations under varying environmental and operational conditions.

Discrete Event Simulation and Real Time Locating Systems

2012 ◽  
Vol 4 (4) ◽  
pp. 16-28
Author(s):  
T. Eugene Day ◽  
Ajit N. Babu ◽  
Steven M. Kymes ◽  
Nathan Ravi
Keyword(s):  
Health Care ◽  
Real Time ◽  
Discrete Event Simulation ◽  
Medical Center ◽  
Discrete Event ◽  
Healthcare Delivery ◽  
The United States ◽  
Careful Consideration ◽  
Health Administration ◽  
Event Simulation

The Veteran’s Health Administration (VHA) is the largest integrated health care system in the United States, forming the arm of the Department of Veterans Affairs (VA) that delivers medical services. From a troubled past, the VHA today is regarded as a model for healthcare transformation. The VA has evaluated and adopted a variety of cutting-edge approaches to foster greater efficiency and effectiveness in healthcare delivery as part of their systems redesign initiative. This paper discusses the integration of two health care analysis platforms: Discrete Event Simulation (DES), and Real Time Locating systems (RTLS) presenting examples of work done at the St. Louis VA Medical Center. Use of RTLS data for generation and validation of DES models is detailed, with prescriptive discussion of methodologies. The authors recommend the careful consideration of these relatively new approaches which show promise in assisting systems redesign initiatives across the health care spectrum.

scholarly journals Data Analytics and Its Advantages for Addressing the Complexity of Healthcare: A Simulated Zika Case Study Example

2019 ◽  
Vol 9 (11) ◽  
pp. 2208 ◽  
Author(s):  
Lily Popova Zhuhadar ◽  
Evelyn Thrasher
Keyword(s):  
Discrete Event Simulation ◽  
Data Analytics ◽  
Business Models ◽  
Discrete Event ◽  
Simulation Models ◽  
Resource Planning ◽  
The United States ◽  
Wait Times ◽  
Event Simulation ◽  
Use Of Data

The need to control rising costs in healthcare has led to an increase in the use of data analytics to develop more efficient healthcare business models. This article discusses a simulation that uses data analytics to minimize the number of physicians and nurses needed in healthcare facilities during a crisis situation. Using a hypothetical emergency scenario, the hospital uses a healthcare analytical system to predict the necessary resources to govern the situation. Based on historical data regarding the flow of patients through the facility, a discrete-event simulation estimates resource scheduling and the resulting impact on both wait times and personnel demand. Furthermore, the value of multiple replications for discrete-event simulation models is discussed and defined, along with factors that enable greater control of multiple design points with this simulated experiment. The results of this study demonstrate the value of simulation modeling in effective resource planning. The addition of only a single doctor significantly reduced predicted wait times for patients during the crisis. Further, the findings support the use of data analytics and predictive modeling to mitigate rising healthcare costs in the United States through efficient planning and resource allocation.

scholarly journals Bayesian-based pipe failure model

2004 ◽  
Vol 6 (4) ◽  
pp. 259-264 ◽  
Author(s):  
T. G. Watson ◽  
C. D. Christian ◽  
A. J. Mason ◽  
M. H. Smith ◽  
R. Meyer
Keyword(s):  
Discrete Event Simulation ◽  
Bayesian Approach ◽  
Distribution Systems ◽  
Discrete Event ◽  
Object Oriented ◽  
Event Simulation ◽  
Maintenance Policies ◽  
Term Management ◽  
The Bayesian Approach

The efficient long term management of large-scale public funded assets is an area of growing importance. Ageing infrastructure, growth and limited capital all result in the need for a more robust and rigorous methodology to prioritise rehabilitation and renewal decisions and, as importantly, to forecast future expenditure requirements. The overall objective of this research is to develop a Bayesian-based decision support system that will facilitate the identification of efficient asset management policies. The Bayesian approach enables us to formally incorporate, express and update our uncertainty when determining such policies. This is particularly relevant for water utilities that have incomplete or unreliable historical failure data sets and, as a consequence, rely heavily on past engineering experience. An object oriented discrete event simulation has been developed to analyse existing maintenance policies, test the Bayesian methodology and to develop and identify improved maintenance policies. This paper focuses on the areas of research relating to the long term management of water distribution systems and, in particular, will present: (1) an overview of the Bayesian approach, (2) development and initial results for an object oriented discrete event simulation and (3) proposed future research and development.

scholarly journals Supporting scale-up of COVID-19 RT-PCR testing processes with discrete event simulation

PLoS ONE ◽  
2021 ◽  
Vol 16 (7) ◽  
pp. e0255214
Author(s):  
Jad El Hage ◽  
Patti Gravitt ◽  
Jacques Ravel ◽  
Nadia Lahrichi ◽  
Erica Gralla
Keyword(s):  
Discrete Event Simulation ◽  
Discrete Event ◽  
Scale Up ◽  
Simulation Models ◽  
The United States ◽  
Molecular Testing ◽  
Rt Pcr ◽  
Event Simulation ◽  
Trade Offs ◽  
The Impact

Testing is critical to mitigating the COVID-19 pandemic, but testing capacity has fallen short of the need in the United States and elsewhere, and long wait times have impeded rapid isolation of cases. Operational challenges such as supply problems and personnel shortages have led to these bottlenecks and inhibited the scale-up of testing to needed levels. This paper uses operational simulations to facilitate rapid scale-up of testing capacity during this public health emergency. Specifically, discrete event simulation models were developed to represent the RT-PCR testing process in a large University of Maryland testing center, which retrofitted high-throughput molecular testing capacity to meet pandemic demands in a partnership with the State of Maryland. The simulation models support analyses that identify process steps which create bottlenecks, and evaluate “what-if” scenarios for process changes that could expand testing capacity. This enables virtual experimentation to understand the trade-offs associated with different interventions that increase testing capacity, allowing the identification of solutions that have high leverage at a feasible and acceptable cost. For example, using a virucidal collection medium which enables safe discarding of swabs at the point of collection removed a time-consuming “deswabbing” step (a primary bottleneck in this laboratory) and nearly doubled the testing capacity. The models are also used to estimate the impact of demand variability on laboratory performance and the minimum equipment and personnel required to meet various target capacities, assisting in scale-up for any laboratories following the same process steps. In sum, the results demonstrate that by using simulation modeling of the operations of SARS-CoV-2 RT-PCR testing, preparedness planners are able to identify high-leverage process changes to increase testing capacity.

Comparative Effectiveness of Tacrolimus-Based Steroid Sparing versus Steroid Maintenance Regimens in Kidney Transplantation: Results from Discrete Event Simulation

2017 ◽  
Vol 37 (7) ◽  
pp. 827-843 ◽  
Author(s):  
Vibha C. A. Desai ◽  
Yann Ferrand ◽  
Teresa M. Cavanaugh ◽  
Christina M. L. Kelton ◽  
J. Jaime Caro ◽  
...  
Keyword(s):  
Kidney Transplantation ◽  
Adverse Events ◽  
Discrete Event Simulation ◽  
Discrete Event ◽  
Graft Loss ◽  
The United States ◽  
Optimal Timing ◽  
Steroid Withdrawal ◽  
Event Simulation ◽  
Steroid Sparing

Background. Corticosteroids used as immunosuppressants to prevent acute rejection (AR) and graft loss (GL) following kidney transplantation are associated with serious cardiovascular and other adverse events. Evidence from short-term randomized controlled trials suggests that many patients on a tacrolimus-based immunosuppressant regimen can withdraw from steroids without increased AR or GL risk. Objectives. To measure the long-term tradeoff between GL and adverse events for a heterogeneous-risk population and determine the optimal timing of steroid withdrawal. Methods. A discrete event simulation was developed including, as events, AR, GL, myocardial infarction (MI), stroke, cytomegalovirus, and new onset diabetes mellitus (NODM), among others. Data from the United States Renal Data System were used to estimate event-specific parametric regressions, which accounted for steroid-sparing regimen (avoidance, early 7-d withdrawal, 6-mo withdrawal, 12-mo withdrawal, and maintenance) as well as patients’ demographics, immunologic risks, and comorbidities. Regression-equation results were used to derive individual time-to-event Weibull distributions, used, in turn, to simulate the course of patients over 20 y. Results. Patients on steroid avoidance or an early-withdrawal regimen were more likely to experience AR (45.9% to 55.0% v. 33.6%, P < 0.05) and GL (51.5% to 68.8% v. 37.8%, P < 0.05) compared to patients on steroid maintenance. Patients in 6-mo and 12-mo steroid withdrawal groups were less likely to experience MI (11.1% v. 13.3%, P < 0.05), NODM (30.7% to 34.4% v. 37.7%, P < 0.05), and cardiac death (29.9% to 30.5% v. 32.4%, P < 0.05), compared to steroid maintenance. Conclusions. Strategies of 6- and 12-mo steroid withdrawal post-kidney transplantation are expected to reduce the rates of adverse cardiovascular events and other outcomes with no worsening of AR or GL rates compared with steroid maintenance.

scholarly journals Perancangan Perbaikan Pelayanan Bongkar Muat Dermaga X Dengan Menggunakan Extend Simulasi

2019 ◽  
Vol 8 (1) ◽  
pp. 19-26
Author(s):  
Misra Hartati ◽  
Ahmad Kurniawan ◽  
Melfa Yola ◽  
Merry Siska
Keyword(s):  
Discrete Event Simulation ◽  
Large Scale ◽  
Discrete Event ◽  
Simulation Method ◽  
Event Simulation ◽  
Sea Transportation ◽  
Additional Capacity

Large-scale logistics companies deliver products using sea transportation effectively. Company X as one of the pioneer port containers service still has limitations both from minimal stacking capacity and limited equipment, 1 HMC unit and 1 unit reach adapter. The number of containers increases from 2014-2017, but the availability of tools and facilities that needed continue to cause overcapacity problem. This paper aims to determine the yard occupancy ratio (YOR), berth occupancy ratio (BOR) and utility equipment that are in accordance with the standards to prevent overcapacity at port X until 2020. This study uses extend simulation method to make improvements and analysis of conditions that running, the results of the study are recommendations for the addition of 2 units of transport and the addition of reach units of 2 units. For the YOR value, additional capacity from 2,046 TEUs was made to 3,800 TEUs so that the initial maximum YOR was 139.8% to 75.3%, while BOR still in maximum BOR capacity which is 24.0%.Keywords: Container, Discrete Event Simulation, ExtendSim, Port

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