A framework to study the resilience of organizations: a case study of a nuclear emergency plan

El desarrollo de la resiliencia es un campo de investigación importante en ámbitos como el Management, la Ingeniería, la Psicología o la Ecología. La importancia del estudio de la resiliencia se ha visto desarrollada por el aumento tanto de desastres naturales como antropogénicos, así como por el desarrollo de conciencia acerca de sus efectos. Estas razones de peso han influido en que los Gobiernos estén invirtiendo recursos en la mejora de la resiliencia de organizaciones, infraestructuras, ciudades, individuos, etc. Sin embargo, a pesar de su importancia, el número de trabajos de investigación que se centran en el desarrollo de metodologías específicas para el diseño de organizaciones resilientes es reducido. El principal objetivo de esta investigación es mejorar este aspecto introduciendo un marco para el diseño de organizaciones resilientes. Para alcanzar este objetivo, se explica cómo emplear el Modelo de Sistemas Viables para el diseño de estas organizaciones. Nos hemos centrado en uno de los aspectos clave de la resiliencia: las comunicaciones. Para ello, se ha usado el caso de estudio del plan de emergencia de una central nuclear en España. Las comunicaciones en una organización pueden modelarse como un proceso de difusión en redes multiplex. Buscamos arquitecturas aplicables a nuestro caso de estudio. Sin embargo, no se ha encontrado ninguna que cumpliera con los requisitos que se necesitaban. Este hecho, nos ha llevado a proponer una nueva arquitectura, que además de permitir estudiar la difusión de información en una organización, permite estudiar otros procesos de difusión en redes multiplex.Departamento de Organización de Empresas y Comercialización e Investigación de MercadosDoctorado en Ingeniería Industria

Multi-level agent-based modeling - A literature survey

During last decade, multi-level agent-based modeling has received significant and dramatically increasing interest. In this article we present a comprehensive and structured review of literature on the subject. We present the main theoretical contributions and application domains of this concept, with an emphasis on social, flow, biological and biomedical models.Comment: v2. Ref 102 added. v3-4 Many refs and text added v5-6 bibliographic statistics updated. v7 Change of the name of the paper to reflect what it became, many refs and text added, bibliographic statistics update

04041 Abstracts Collection -- Component-Based Modeling and Simulation

From 18.01.04 to 23.01.04, the Dagstuhl Seminar 04041 ``Component-Based Modeling and Simulation\u27\u27 was held in the International Conference and Research Center (IBFI), Schloss Dagstuhl. During the seminar, several participants presented their current research, and ongoing work and open problems were discussed. Abstracts of the presentations given during the seminar as well as abstracts of seminar results and ideas are put together in this paper. The first section describes the seminar topics and goals in general. Links to extended abstracts or full papers are provided, if available

SCS: 60 years and counting! A time to reflect on the Society's scholarly contribution to M&S from the turn of the millennium.

The Society for Modeling and Simulation International (SCS) is celebrating its 60th anniversary this year. Since its inception, the Society has widely disseminated the advancements in the field of modeling and simulation (M&S) through its peer-reviewed journals. In this paper we profile research that has been published in the journal SIMULATION: Transactions of the Society for Modeling and Simulation International from the turn of the millennium to 2010; the objective is to acknowledge the contribution of the authors and their seminal research papers, their respective universities/departments and the geographical diversity of the authors' affiliations. Yet another objective is to contribute towards the understanding of the overall evolution of the discipline of M&S; this is achieved through the classification of M&S techniques and its frequency of use, analysis of the sectors that have seen the predomination application of M&S and the context of its application. It is expected that this paper will lead to further appreciation of the contribution of the Society in influencing the growth of M&S as a discipline and, indeed, in steering its future direction

Testability of a swarm robot using a system of systems approach and discrete event simulation

A simulation framework using discrete event system specification (DEVS) and data encoded with Extensible Markup Language (XML) is presented to support agent-in-the-loop (AIL) simulations for large, complex, and distributed systems. A System of Systems (SoS) approach organizes the complex systems hierarchically. AIL simulations provide a necessary step in maintaining model continuity methods to achieve a greater degree of accuracy in systems analysis. The proposed SoS approach enables the simulation and analysis of these independent and cooperative systems by concentrating on the data transferred among systems to achieve interoperability instead of requiring the software modeling of global state spaces. The information exchanged is wrapped in XML to facilitate system integration and interoperability. A Groundscout is deployed as a real agent working cooperatively with virtual agents to form a robotic swarm in an example threat detection scenario. This scenario demonstrates the AIL framework\u27s ability to successfully test a swarm robot for individual performance and swarm behavior. Results of the testing process show an increase of robot team size increases the rate of successfully investigating a threat while critical violations of the algorithm remained low despite packet loss

Understanding the Impact of Large-Scale Power Grid Architectures on Performance

Grid balancing is a critical system requirement for the power grid in matching the supply to the demand. This balancing has historically been achieved by conventional power generators. However, the increasing level of renewable penetration has brought more variability and uncertainty to the grid (Ela, Diakov et al. 2013, Bessa, Moreira et al. 2014), which has considerable impacts and implications on power system reliability and efficiency, as well as costs. Energy planners have the task of designing infrastructure power systems to provide electricity to the population, wherever and whenever needed. Deciding of the right grid architecture is no easy task, considering consumers’ economic, environmental, and security priorities, while making efficient use of existing resources. In this research, as one contribution, we explore associations between grid architectures and their performance, that is, their ability to meet consumers’ concerns. To do this, we first conduct a correlation analysis study. We propose a generative method that captures path dependency by iteratively creating grids, structurally different. The method would generate alternative grid architectures by subjecting an initial grid to a heuristic choice method for decision making over a fixed time horizon. Second, we also conduct a comparative study to evaluate differences in grid performances. We consider two balancing area operation types, presenting different structures and coordination mechanisms. Both studies are performed with the use of a grid simulation model, Spark! The aim of this model is to offer a meso-scale solution that enables the study of very large power systems over long-time horizons, with a sufficient level of fidelity to perform day-to-day grid activities and support architectural questions about the grids of the future. More importantly, the model reconciles long-term planning with short-term grid operations, enabling long-term projections validation via grid operations and response on a daily basis. This is our second contribution

A model-based approach to System of Systems risk management

The failure of many System of Systems (SoS) enterprises can be attributed to the inappropriate application of traditional Systems Engineering (SE) processes within the SoS domain, because of the mistaken belief that a SoS can be regarded as a single large, or complex, system. SoS Engineering (SoSE) is a sub-discipline of SE; Risk Management and Modelling and Simulation (M&S) are key areas within SoSE, both of which also lie within the traditional SE domain. Risk Management of SoS requires a different approach to that currently taken for individual systems; if risk is managed for each component system then it cannot be assumed that the aggregated affect will be to mitigate risk at the SoS level. A literature review was undertaken examining three themes: (1) SoS Engineering (SoSE), (2) M&S and (3) Risk. Theme 1 of the literature provided insight into the activities comprising SoSE and its difference from traditional SE with risk management identified as a key activity. The second theme discussed the application of M&S to SoS, providing an output, which supported the identification of appropriate techniques and concluding that, the inherent complexity of a SoS required the use of M&S in order to support SoSE activities. Current risk management approaches were reviewed in theme 3 as well as the management of SoS risk. Although some specific examples of the management of SoS risk were found, no mature, general approach was identified, indicating a gap in current knowledge. However, it was noted most of these examples were underpinned by M&S approaches. It was therefore concluded a general approach SoS risk management utilising M&S methods would be of benefit. In order to fill the gap identified in current knowledge, this research proposed a new model based approach to Risk Management where risk identification was supported by a framework, which combined SoS system of interest dimensions with holistic risk types, where the resulting risks and contributing factors are captured in a causal network. Analysis of the causal network using a model technique selection tool, developed as part of this research, allowed the causal network to be simplified through the replacement of groups of elements within the network by appropriate supporting models. The Bayesian Belief Network (BBN) was identified as a suitable method to represent SoS risk. Supporting models run in Monte Carlo Simulations allowed data to be generated from which the risk BBNs could learn, thereby providing a more quantitative approach to SoS risk management. A method was developed which provided context to the BBN risk output through comparison with worst and best-case risk probabilities. The model based approach to Risk Management was applied to two very different case studies: Close Air Support mission planning and the Wheat Supply Chain, UK National Food Security risks, demonstrating its effectiveness and adaptability. The research established that the SoS SoI is essential for effective SoS risk identification and analysis of risk transfer, effective SoS modelling requires a range of techniques where suitability is determined by the problem context, the responsibility for SoS Risk Management is related to the overall SoS classification and the model based approach to SoS risk management was effective for both application case studies

A Review of Platforms for the Development of Agent Systems

Agent-based computing is an active field of research with the goal of building autonomous software of hardware entities. This task is often facilitated by the use of dedicated, specialized frameworks. For almost thirty years, many such agent platforms have been developed. Meanwhile, some of them have been abandoned, others continue their development and new platforms are released. This paper presents a up-to-date review of the existing agent platforms and also a historical perspective of this domain. It aims to serve as a reference point for people interested in developing agent systems. This work details the main characteristics of the included agent platforms, together with links to specific projects where they have been used. It distinguishes between the active platforms and those no longer under development or with unclear status. It also classifies the agent platforms as general purpose ones, free or commercial, and specialized ones, which can be used for particular types of applications.Comment: 40 pages, 2 figures, 9 tables, 83 reference