20,693 research outputs found

    How Resilient Are Our Societies? Analyses, Models, and Preliminary Results

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    Traditional social organizations such as those for the management of healthcare and civil defence are the result of designs and realizations that matched well with an operational context considerably different from the one we are experiencing today: A simpler world, characterized by a greater amount of resources to match less users producing lower peaks of requests. The new context reveals all the fragility of our societies: unmanageability is just around the corner unless we do not complement the "old recipes" with smarter forms of social organization. Here we analyze this problem and propose a refinement to our fractal social organizations as a model for resilient cyber-physical societies. Evidence to our claims is provided by simulating our model in terms of multi-agent systems.Comment: Paper submitted for publication in the Proc. of SERENE 2015 (http://serene.disim.univaq.it/2015/

    Case study: The use of petrol stations to fuel supply in the event of a power outage

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    Long-term power outages represent a significant interference with the lives of citizens, institutions, and sector of critical infrastructure. One segment of critical infrastructure is healthcare. In this sector, it is essential to maintain functionality and provide ongoing healthcare to clients. At the time of power failure, alternative power sources are used in these facilities for which fuel supply is required. The aim of the paper is to analyze fuel filling stations for hospitals in the event of a power outage. The paper describes the use of petrol stations at the time of failure. Also, an analysis is carried out at a selected hospital regarding fuel supply and the determination of service stations for their supply. The PTV Vissim software will be used to analyze critical junction points for supply. At the end of the paper recommendations for the selected hospital will be proposed. © 2019 The Authors. Published by Elsevier B.V.Internal grant agency of Tomas Bata University in Zlin [IGA/FAI/2019/001]; Depatrment of Security Engeneering, Faculty of Applied Informatic

    Extendsim-based research on transport process optimization of emergency Cold-chain Logistics

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    A Framework for Developing and Integrating Effective Routing Strategies Within the Emergency Management Decision-Support System, Research Report 11-12

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    This report describes the modeling, calibration, and validation of a VISSIM traffic-flow simulation of the San José, California, downtown network and examines various evacuation scenarios and first-responder routings to assess strategies that would be effective in the event of a no-notice disaster. The modeled network required a large amount of data on network geometry, signal timings, signal coordination schemes, and turning-movement volumes. Turning-movement counts at intersections were used to validate the network with the empirical formula-based measure known as the GEH statistic. Once the base network was tested and validated, various scenarios were modeled to estimate evacuation and emergency vehicle arrival times. Based on these scenarios, a variety of emergency plans for San José’s downtown traffic circulation were tested and validated. The model could be used to evaluate scenarios in other communities by entering their community-specific data

    Supply chain management of blood products: a literature review.

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    This paper presents a review of the literature on inventory and supply chain management of blood products. First, we identify different perspectives on approaches to classifying the existing material. Each perspective is presented as a table in which the classification is displayed. The classification choices are exemplified through the citation of key references or by expounding the features of the perspective. The main contribution of this review is to facilitate the tracing of published work in relevant fields of interest, as well as identifying trends and indicating which areas should be subject to future research.OR in health services; Supply chain management; Inventory; Blood products; Literature review;

    Assessing vulnerability and modelling assistance: using demographic indicators of vulnerability and agent-based modelling to explore emergency flooding relief response

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    Flooding is a significant concern for much of the UK and is recognised as a primary threat by most local councils. Those in society most often deemed vulnerable: the elderly, poor or sick, for example, often see their level of vulnerability increase during hazard events. A greater knowledge of the spatial distribution of vulnerability within communities is key to understanding how a population may be impacted by a hazard event. Vulnerability indices are regularly used – in conjunction with needs assessments and on-the-ground research – to target service provision and justify resource allocation. Past work on measuring and mapping vulnerability has been limited by a focus on income-related indicators, a lack of consideration of accessibility, and the reliance on proprietary data. The Open Source Vulnerability Index (OSVI) encompasses an extensive range of vulnerability indicators supported by the wider literature and expert validation and provides data at a sufficiently fine resolution that can identify vulnerable populations. Findings of the OSVI demonstrate the potential cascading impact of a flood hazard as it impacts an already vulnerable population: exacerbating pre-existing vulnerabilities, limiting capabilities and restricting accessibility and access to key services. The OSVI feeds into an agent-based model (ABM) that explores the capacity of the British Red Cross (BRC) to distribute relief during flood emergencies using strategies based upon the OSVI. A participatory modelling approach was utilised whereby the BRC were included in all aspects of the model development. The major contribution of this work is the novel synthesis of demographics analysis, vulnerability mapping and geospatial simulation. The project contributes to the growing understanding of vulnerability and response management within the NGO sector. It is hoped that the index and model produced will allow responder organisations to run simulations of similar emergency events and adjust strategic response plans accordingly

    Quantifying restoration costs in the aftermath of an extreme event using system dynamics and dynamic mathematical modeling approaches

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    Extreme events such as earthquakes, hurricanes, and the like, lead to devastating effects that may render multiple supply chain critical infrastructure elements inoperable. The economic losses caused by extreme events continue well after the emergency response phase has ended and are a key factor in determining the best path for post-disaster restoration. It is essential to develop efficient restoration and disaster management strategies to ameliorate the losses from such events. This dissertation extends the existing knowledge base on disaster management and restoration through the creation of models and tools that identify the relationship between production losses and restoration costs. The first research contribution is a system dynamics inoperability model that determines inputs, outputs, and flows for roadway networks. This model can be used to identify the connectivity of road segments and better understand how inoperability contributes to economic consequences. The second contribution is an algorithm that integrates critical infrastructure data derived from bottom-up cost estimation technique as part of an object-oriented software tool that can be used to determine the impact of system disruptions. The third contribution is a dynamic mathematical model that establishes a framework to estimate post-disaster restoration costs from a whole system perspective. Engineering managers, city planners, and policy makers can use the methodologies developed in this research to develop effective disaster planning schemas and to prioritize post-disaster restoration operations --Abstract, page iv

    Strategies for dynamic appointment making by container terminals

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    We consider a container terminal that has to make appointments with barges dynamically, in real-time, and partly automatic. The challenge for the terminal is to make appointments with only limited knowledge about future arriving barges, and in the view of uncertainty and disturbances, such as uncertain arrival and handling times, as well as cancellations and no-shows. We illustrate this problem using an innovative implementation project which is currently running in the Port of Rotterdam. This project aims to align barge rotations and terminal quay schedules by means of a multi-agent system. In this\ud paper, we take the perspective of a single terminal that will participate in this planning system, and focus on the decision making capabilities of its intelligent agent. We focus on the question how the terminal operator can optimize, on an operational level, the utilization of its quay resources, while making reliable appointments with barges, i.e., with a guaranteed departure time. We explore two approaches: (i) an analytical approach based on the value of having certain intervals within the schedule and (ii) an approach based on sources of exibility that are naturally available to the terminal. We use simulation to get insight in the benefits of these approaches. We conclude that a major increase in utilization degree could be achieved only by deploying the sources of exibility, without harming the waiting time of barges too much
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