A spatial queuing model for the location decision of emergency medical vehicles for pandemic outbreaks: the case of Za'atari refugee camp

2021 ◽  
Vol ahead-of-print (ahead-of-print) ◽  
Author(s):  
Felix Blank
Keyword(s):  
Queuing Theory ◽  
Emergency Service ◽  
Performance Metrics ◽  
Service System ◽  
Refugee Camps ◽  
Location Decision ◽  
Stress Tests ◽  
Queuing Model ◽  
Content Type ◽  
Emergency Medical

PurposeRefugee camps can be severely struck by pandemics, like potential COVID-19 outbreaks, due to high population densities and often only base-level medical infrastructure. Fast responding medical systems can help to avoid spikes in infections and death rates as they allow the prompt isolation and treatment of patients. At the same time, the normal demand for emergency medical services has to be dealt with as well. The overall goal of this study is the design of an emergency service system that is appropriate for both types of demand.Design/methodology/approachA spatial hypercube queuing model (HQM) is developed that uses queuing-theory methods to determine locations for emergency medical vehicles (also called servers). Therefore, a general optimization approach is applied, and subsequently, virus outbreaks at various locations of the study areas are simulated to analyze and evaluate the solution proposed. The derived performance metrics offer insights into the behavior of the proposed emergency service system during pandemic outbreaks. The Za'atari refugee camp in Jordan is used as a case study.FindingsThe derived locations of the emergency medical system (EMS) can handle all non-virus-related emergency demands. If additional demand due to virus outbreaks is considered, the system becomes largely congested. The HQM shows that the actual congestion is highly dependent on the overall amount of outbreaks and the corresponding case numbers per outbreak. Multiple outbreaks are much harder to handle even if their cumulative average case number is lower than for one singular outbreak. Additional servers can mitigate the described effects and lead to enhanced resilience in the case of virus outbreaks and better values in all considered performance metrics.Research limitations/implicationsSome parameters that were assumed for simplification purposes as well as the overall model should be verified in future studies with the relevant designers of EMSs in refugee camps. Moreover, from a practitioners perspective, the application of the model requires, at least some, training and knowledge in the overall field of optimization and queuing theory.Practical implicationsThe model can be applied to different data sets, e.g. refugee camps or temporary shelters. The optimization model, as well as the subsequent simulation, can be used collectively or independently. It can support decision-makers in the general location decision as well as for the simulation of stress-tests, like virus outbreaks in the camp area.Originality/valueThe study addresses the research gap in an optimization-based design of emergency service systems for refugee camps. The queuing theory-based approach allows the calculation of precise (expected) performance metrics for both the optimization process and the subsequent analysis of the system. Applied to pandemic outbreaks, it allows for the simulation of the behavior of the system during stress-tests and adds a further tool for designing resilient emergency service systems.

scholarly journals The operation of an Emergency Medical Department in a county hospital from a logistic point of view

2014 ◽  
Vol 8 (2) ◽  
pp. 109-113
Author(s):  
Gábor Markó ◽  
József Gál
Keyword(s):  
Emergency Department ◽  
Emergency Service ◽  
Service System ◽  
The United States ◽  
Point Of View ◽  
Medical Department ◽  
Emergency Medical ◽  
The One ◽  
Medical Attendance ◽  
The University

The purpose of this article is to give an overview of the actual emergency medical attendance through an exemplary hospital in Hungary, highlighting its possible imperfections which could perhaps be improved through further structural developments. In order to be expressive, the article follows through the journey of two nominal patients who turned up in the emergency department of the hospital. The importance of this topic is expressed by the fitful judgment of the emergency attendance. Emergency service had already existed in the United States, only later then did the one-entrance service system start to develop Hungary. In some places this system has been working well for decades, but for instance at the University of Szeged – due to the uncertain judgment of the system – the construction is just being finalized, right at the time when such studies are published that question the reason of existence of the emergency departments – at least in their actual form.

scholarly journals Performance Analysis of D2D Communication with Retransmission Mechanism in Cellular Networks

2020 ◽  
Vol 10 (3) ◽  
pp. 1097 ◽  
Author(s):  
Jianfang Xin ◽  
Qi Zhu ◽  
Guangjun Liang ◽  
Tianjiao Zhang
Keyword(s):  
Performance Analysis ◽  
Cellular Networks ◽  
Queuing Theory ◽  
Performance Metrics ◽  
Embedded Markov Chain ◽  
Data Generation ◽  
Queuing Model ◽  
Average Delay ◽  
Dropping Probability ◽  
Retransmission Mechanism

In this paper, we focus on the performance analysis of device-to-device (D2D) underlay communication in cellular networks. First, we develop a spatiotemporal traffic model to model a retransmission mechanism for D2D underlay communication. The D2D users in backlogged statuses are modeled as a thinned Poisson point process (PPP). To capture the characteristics of sporadic wireless data generation and limited buffer, we adopt queuing theory to analyze the performance of dynamic traffic. Furthermore, a feedback queuing model is adopted to analyze the performance with retransmission strategy. With the consideration of interference and channel fading, the service probability of the queue departure process is determined by the received signal-to-interference-plus-noise ratio (SINR). Then, the embedded Markov chain is employed to depict the queuing status in the D2D user buffer. We compute its steady-state distribution and derive the closed-form expressions of performance metrics, namely the average queue length, average throughput, average delay, and dropping probability. Simulation results show the validity and rationality of the theoretical analysis with different channel parameters and D2D densities. In addition, the simulation explores the dropping probability of a D2D user with and without the retransmission strategy for different D2D links in the system. When the arrival rate is comparatively high, the optimal throughput is reached after fewer retransmission attempts as a result of the limited buffer.

Using queuing theory to solve the problem of momentum to issuing the driving licenses in Dohuk city

2019 ◽  
Vol 8 (4) ◽  
pp. 136
Author(s):  
Nabeel G. Nacy ◽  
Samaher T. Ibrahim
Keyword(s):  
Poisson Distribution ◽  
Customer Service ◽  
Queuing Theory ◽  
Performance Metrics ◽  
Service System ◽  
Service Demand ◽  
The Cost ◽  
Number Of Customers ◽  
System Power ◽  
Waiting Lines

Queuing theory is a mathematical study of so-called queues or waiting lines. This phenomenon is common in daily life as in gas stations, airports, repair workshops and other common everyday examples. Waiting occurs when service demand is higher than service system power. Due to the difficulty in predicting the number of customers arriving and the time taken by the customer at the service station, the process of obtaining performance metrics is necessary before the queuing systems are implemented. When the service system power is too high, the system is charged at a high cost. Conversely, when the system power is low (insufficient for the customer service), the waiting time in the queue increases, As well as loss of order to its customers. Therefore, attention has been drawn to the so-called theory of waiting lines to solve such problems to reach a balance in the work of the system. This research aims to overcome the difficulties experienced by citizens in obtaining market holidays on time and reduce waste in time and the cost of waiting. The results were as shown in tables (l) to (6) of the city center and according to the distribution of access and service of the model used (G / G / C). We note in the Poisson distribution with exponential that the average number of customers in the system Ls = 5.527), which is approximately (5 customers), which is waiting in the system. We note in the previous distribution itself that the average number of customers in the waiting queue (customer 2.1924 = L q) is approximately 2 (customer) which is waiting in queue. The Poisson distribution with the exponential is that the average time spent by the customer in the system (minute W s = 16.5772). Note in the Poisson distribution with the exponential that the average time spent by the customer in the waiting queue is (minute W = 6.5772) We note in the Poisson distribution with exponential that The average number of customers in the system (customer Ls = 4.3258) is about (4 customers) which is waiting in the system. We see in the previous distribution itself that the average number of customers in the queue (customer 2.0 = L q) ) There is no waiting in the queue. The Poisson distribution with exponential is the average time spent by the customer in the system (min W s = 11.3333). We note in the Poisson distribution with exponential that the average time spent by the customer in the waiting queue is (min W q = 4.6666)

Predictive Data Center Selection Scheme for Response Time Optimization in Cloud Computing

2021 ◽  
Vol 11 (1) ◽  
pp. 93-111
Author(s):  
Deepak Kapgate
Keyword(s):  
Cloud Computing ◽  
Response Time ◽  
Data Center ◽  
Queuing Theory ◽  
Performance Metrics ◽  
Forecasting Model ◽  
Selection Algorithm ◽  
Queuing Model ◽  
Selection Scheme ◽  
Selection Algorithms

The quality of cloud computing services is evaluated based on various performance metrics out of which response time (RT) is most important. Nearly all cloud users demand its application's RT as minimum as possible, so to minimize overall system RT, the authors have proposed request response time prediction-based data center (DC) selection algorithm in this work. Proposed DC selection algorithm uses results of optimization function for DC selection formulated based on M/M/m queuing theory, as present cloud scenario roughly obeys M/M/m queuing model. In cloud environment, DC selection algorithms are assessed based on their performance in practice, rather than how they are supposed to be used. Hence, explained DC selection algorithm with various forecasting models is evaluated for minimum user application RT and RT prediction accuracy on various job arrival rates, real parallel workload types, and forecasting model training set length. Finally, performance of proposed DC selection algorithm with optimal forecasting model is compared with other DC selection algorithms on various cloud configurations.

Improving Productivity: An Emergency Service System in Which Cross-Trained Fire-Medics Respond to Medical Calls and Fire Incidents

2019 ◽  
Author(s):  
Cheng Hua ◽  
Arthur Swersey ◽  
Fernando Chiyoshi ◽  
Ana Paula Iannoni ◽  
Reinaldo Morabito
Keyword(s):  
Emergency Service ◽  
Service System

Evaluation of subway passengers transfer hub congestion based on queuing model and TOPSIS method

2021 ◽  
pp. 1-22
Author(s):  
Xiaokun Wang ◽  
Dong Ni
Keyword(s):  
Queuing Theory ◽  
Evaluation Model ◽  
Flow Characteristics ◽  
Distribution Area ◽  
Flow Density ◽  
Topsis Method ◽  
Queuing Model ◽  
Service Facility ◽  
Passenger Flow ◽  
Topsis Technique

To scientifically and reasonably evaluate and pre-warn the congestion degree of subway transfer hub, and effectively know the risk of subway passengers before the congestion time coming. We analyzed the passenger flow characteristics of various service facilities in the hub. The congested area of the subway passenger flow interchange hub is divided into queuing area and distribution area. The queuing area congestion evaluation model selects M/M/C and M/G/C based on queuing theory. The queuing model and the congestion evaluation model of the distribution area select the TOPSIS (Technique for Order Preference by Similarity to Ideal Solution) method. Queue length and waiting time are selected as the evaluation indicators of congestion in the queuing area, and passenger flow, passenger flow density and walking speed are selected as the evaluation indicators of congestion in the distribution area. And then, K-means cluster analysis method is used to analyze the sample data, and based on the selected evaluation indicators and the evaluation model establishes the queuing model of the queuing area and the TOPSIS model of the collection and distribution area. The standard value of the congestion level of various service facilities and the congestion level value of each service facility obtained from the evaluation are used as input to comprehensively evaluate the overall congestion degree of the subway interchange hub. Finally we take the Xi’an Road subway interchange hub in Dalian as empirical research, the data needed for congestion evaluation was obtained through field observations and questionnaires, and the congestion degree of the queue area and the distribution area at different times of the workday was evaluated, and the congestion of each service facility was evaluated. The grade value is used as input, and the TOPSIS method is used to evaluate the degree of congestion in the subway interchange hub, which is consistent with the results of passenger congestion in the questionnaire, which verifies the feasibility of the evaluation model and method.

Autonomous evolution of service system in cluster supply chain

Kybernetes ◽  
2015 ◽  
Vol 44 (1) ◽  
pp. 139-158
Author(s):  
Xiao Xue ◽  
Shufang Wang ◽  
Hao Chao
Keyword(s):  
Supply Chain ◽  
Service Composition ◽  
Service System ◽  
Evaluation Model ◽  
Service Component ◽  
Evolution Mechanism ◽  
Content Type ◽  
External Customer ◽  
Qos Evaluation ◽  
Autonomous Evolution

Purpose – The purpose of this paper is to provide strong theoretical and technical support for the dynamic evolution of service system in “Cluster Supply Chain”(CSC), which can deal with two kinds of context changes: the internal service component changes and the external customer requirement changes. Design/methodology/approach – A “feedback-based” evolution mechanism of service system for CSC is proposed in this study. By means of the feedback update of enterprise service’s Quality of Service (QoS) attribute and the adjustment of the assumed QoS evaluation model, the evolution of service system can be achieved to suit the dynamic market demands. Findings – Results of the study suggest: by means of the “feed-back” evolution mechanism of service system, the enterprises in CSC can handle the context changes effectively to maintain the optimized operation status. Practical implications – The implementation of evolution mechanism in service system can keep the effectiveness of enterprise service composition to face the frequent service component changes and the unpredictable market turbulence. Originality/value – This paper proposes a method to realize the autonomous evolution of service system in CSC, which can support the flexibility and adaptability of enterprise service composition in the changing environment.

Solvency stress testing of Islamic commercial banks

2016 ◽  
Vol 7 (2) ◽  
pp. 112-147 ◽  
Author(s):  
Jamshaid Anwar Chattha ◽  
Simon Archer
Keyword(s):  
Commercial Banks ◽  
Stress Testing ◽  
Profit Sharing ◽  
Capital Requirements ◽  
Capital Adequacy ◽  
Stress Tests ◽  
Regulatory Requirement ◽  
Content Type ◽  
Numerical Example ◽  
Remedial Actions

Purpose This paper aims to provide a methodology for designing and conducting solvency stress tests, under the standardised approach as per IFSB-15, including the establishment of macro-financial links, running scenarios with variation of assumptions and stress scenario parameters; apply and illustrate this methodology by providing a stylised numerical example through a tractable Excel-based framework, through which Islamic Commercial Banks (ICBs) can introduce additional regulatory requirements and show that they would remain in compliance with all capital requirements after a moderate to severe shock; and identify the potential remedial actions that can be envisaged by an ICB. Design/methodology/approach The paper uses the data of the one of the groups to which certain amendments and related assumptions are applied to develop a stylised numerical example for solvency stress-testing purposes. The example uses a Stress Testing Matrix (STeM; a step-by-step approach) to illustrate the stress-testing process. The methodology of the paper uses a two-stage process. The first stage consists of calculating the capital adequacy ratio (CAR) of the ICB using the IFSB formulae, depending on how the profit sharing investment account (PSIA) are treated in the respective jurisdiction. The second stage is the application of the stress scenarios and shocks. Findings Taking into account the specificities of ICBs such as their use of PSIA, the results highlighted the sensitivity of the CAR of an ICB with respect to the changes in the values of alpha and the proportion of unrestricted PSIA on the funding side. The simulation also indicated that an ICB operating above the minimum CAR could be vulnerable to shocks of various degrees of gravity, thus bringing the CAR below the minimum regulatory requirement and necessitating appropriate remedial actions. Practical implications The paper highlights various implications and relationships arising out of stress testing for ICBs, including the vulnerability of an ICB under defined scenarios, demanding appropriate immediate remedial actions on future capital resources and capital needs. The findings of the paper provide a preliminary discussion on developing a comprehensive toolkit for the ICBs similar to what is developed by the International Monetary Fund Financial Sector Assessment Programme. Originality/value This paper focuses on the gap with respect to the stress testing of capital adequacy. The main contribution of the paper is twofold. The first is the development of an STeM – a step-by-step approach, which provides a method for simulating solvency (i.e. capital adequacy) stress tests for ICBs; the second is the demonstration of the potentially crucial impact of profit-sharing investment accounts and the way they are managed by ICBs (notably the smoothing of profit payouts) in assessing the capital adequacy of the ICBs.

Sign in / Sign up

Export Citation Format

Share Document