1,602 research outputs found

    On the characterization of the domination of a diameter-constrained network reliability model

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    AbstractLet G=(V,E) be a digraph with a distinguished set of terminal vertices K⊆V and a vertex s∈K. We define the s,K-diameter of G as the maximum distance between s and any of the vertices of K. If the arcs fail randomly and independently with known probabilities (vertices are always operational), the diameter-constrained s,K-terminal reliability of G, Rs,K(G,D), is defined as the probability that surviving arcs span a subgraph whose s,K-diameter does not exceed D.The diameter-constrained network reliability is a special case of coherent system models, where the domination invariant has played an important role, both theoretically and for developing algorithms for reliability computation. In this work, we completely characterize the domination of diameter-constrained network models, giving a simple rule for computing its value: if the digraph either has an irrelevant arc, includes a directed cycle or includes a dipath from s to a node in K longer than D, its domination is 0; otherwise, its domination is -1 to the power |E|-|V|+1. In particular this characterization yields the classical source-to-K-terminal reliability domination obtained by Satyanarayana.Based on these theoretical results, we present an algorithm for computing the reliability

    On the characterization of the source-to-all-terminal diameter-constrained reliability domination

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    Let G = (V;E) be a digraph with a distinguished set of terminal vertices K V and a vertex s 2 K . We de ne the s;K-diameter of G as the maximum distance between s and any of vertices of K. If the arcs fail randomly and independently with known probabilities (vertices are always operational), the Diameter-constrained s;K-terminal reliability of G, Rs;K(G;D), is de ned as the probability that surviving arcs span a subgraph whose s;K- diameter does not exceed D [5, 11]. A graph invariant called the domination of a graph G was introduced by Satyanarayana and Prabhakar [13] to generate the non-canceling terms of the classical reliability expres- sion, Rs;K(G), based on the same reliability model (i.e. arcs fail randomly and indepen- dently and where nodes are perfect), and de ned as the probability that the surviving arcs span a subgraph of G with unconstrained nite s;K-diameter. This result allowed the generation of rapid algorithms for the computation of Rs;K(G). In this paper we present a characterization of the diameter-constrained s;K-terminal reliability domination of a digraph G = (V;E) with terminal set K = V , and for any diameter bound D, and, as a result, we solve the classical reliability domination, as a speci c case. Moreover we also present a rapid algorithm for the evaluation of Rs;V (G;D).Eje: Teoría (TEOR)Red de Universidades con Carreras en Informática (RedUNCI

    On the characterization of the source-to-all-terminal diameter-constrained reliability domination

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    Let G = (V;E) be a digraph with a distinguished set of terminal vertices K V and a vertex s 2 K . We de ne the s;K-diameter of G as the maximum distance between s and any of vertices of K. If the arcs fail randomly and independently with known probabilities (vertices are always operational), the Diameter-constrained s;K-terminal reliability of G, Rs;K(G;D), is de ned as the probability that surviving arcs span a subgraph whose s;K- diameter does not exceed D [5, 11]. A graph invariant called the domination of a graph G was introduced by Satyanarayana and Prabhakar [13] to generate the non-canceling terms of the classical reliability expres- sion, Rs;K(G), based on the same reliability model (i.e. arcs fail randomly and indepen- dently and where nodes are perfect), and de ned as the probability that the surviving arcs span a subgraph of G with unconstrained nite s;K-diameter. This result allowed the generation of rapid algorithms for the computation of Rs;K(G). In this paper we present a characterization of the diameter-constrained s;K-terminal reliability domination of a digraph G = (V;E) with terminal set K = V , and for any diameter bound D, and, as a result, we solve the classical reliability domination, as a speci c case. Moreover we also present a rapid algorithm for the evaluation of Rs;V (G;D).Eje: Teoría (TEOR)Red de Universidades con Carreras en Informática (RedUNCI

    Domination Invariant of a Diameter Constrained Network Reliability Model

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    Let G=(V,E) be a digraph with a distinguished set of terminal vertices K in V and a vertex s in K. We define the s,K-diameter of G as the maximum distance between s and any of vertices of K. If the arcs fail randomly and independently with known probabilities (vertices are always operational), the Diameter-constrained s,K-terminal reliability of G, R_\{s,K\}(G,D) is defined as the probability that surviving arcs span a subgraph whose s,K-diameter does not exceed D. The Diameter-constrained network reliability is a special case of coherent system models, where the domination invariant has played an important role, both theoretically and for developing algorithms for reliability computation. In this work, we completely characterize the domination of diameter-constrained network models, giving a simple rule for computing its value: if the digraph either has an irrelevant edge, includes a dicycle or includes a dipath from ss to a node in K longer than D, its domination is 0; otherwise, its domination is -1 to the power |E|-|V|+1

    Subject index volumes 1–92

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    Methodology for Comparison of Algorithms for Real-World Multi-objective Optimization Problems: Space Surveillance Network Design

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    Space Situational Awareness (SSA) is an activity vital to protecting national and commercial satellites from damage or destruction due to collisions. Recent research has demonstrated a methodology using evolutionary algorithms (EAs) which is intended to develop near-optimal Space Surveillance Network (SSN) architectures in the sense of low cost, low latency, and high resolution. That research is extended here by (1) developing and applying a methodology to compare the performance of two or more algorithms against this problem, and (2) analyzing the effects of using reduced data sets in those searches. Computational experiments are presented in which the performance of five multi-objective search algorithms are compared to one another using four binary comparison methods, each quantifying the relationship between two solution sets in different ways. Relative rankings reveal strengths and weaknesses of evaluated algorithms empowering researchers to select the best algorithm for their specific needs. The use of reduced data sets is shown to be useful for producing relative rankings of algorithms that are representative of rankings produced using the full set

    Propiedades y métodos de cálculo de la confiabilidad diámetro-acotada en redes

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    Tribunal : Kishor S. Trivedi, Guillermo Durán, Sergio Nesmachnow, Reinaldo Vallejos, Gerardo Rubino, Bruno Tuffin.Esta tesis aborda el problema del cálculo y estimación de la confiabilidad de redes con restricción de diámetro (DCR). Este problema es una generalización del cómputo de la confiabilidad clásica de redes (CLR). Se ha dedicado un esfuerzo considerable al estudio de la confiabilidad, debido a la relevancia que dichas métricas han tomado en contexto de redes reales durante los últimos 50 años, y al hecho de que el problema tiene complejidad computacional NP-hard aún bajo fuertes simplificaciones. La restricción de diámetro ha ganado relevancia debido al surgimiento de contextos en los cuales las latencias o número de saltos de los paquetes impactan en el desempeño de la red; por ejemplo voz sobre IP, P2P e interfaces ricas dentro de aplicaciones web

    Optimizing resilience decision-support for natural gas networks under uncertainty

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    2019 Summer.Includes bibliographical references.Community resilience in the aftermath of a hazard requires the functionality of complex, interdependent infrastructure systems become operational in a timely manner to support social and economic institutions. In the context of risk management and community resilience, critical decisions should be made not only in the aftermath of a disaster in order to immediately respond to the destructive event and properly repair the damage, but preventive decisions should to be made in order to mitigate the adverse impacts of hazards prior to their occurrence. This involves significant uncertainty about the basic notion of the hazard itself, and usually involves mitigation strategies such as strengthening components or preparing required resources for post-event repairs. In essence, instances of risk management problems that encourage a framework for coupled decisions before and after events include modeling how to allocate resources before the disruptive event so as to maximize the efficiency for their distribution to repair in the aftermath of the event, and how to determine which network components require preventive investments in order to enhance their performance in case of an event. In this dissertation, a methodology is presented for optimal decision making for resilience assessment, seismic risk mitigation, and recovery of natural gas networks, taking into account their interdependency with some of the other systems within the community. In this regard, the natural gas and electric power networks of a virtual community were modeled with enough detail such that it enables assessment of natural gas network supply at the community level. The effect of the industrial makeup of a community on its natural gas recovery following an earthquake, as well as the effect of replacing conventional steel pipes with ductile HDPE pipelines as an effective mitigation strategy against seismic hazard are investigated. In addition, a multi objective optimization framework that integrates probabilistic seismic risk assessment of coupled infrastructure systems and evolutionary algorithms is proposed in order to determine cost-optimal decisions before and after a seismic event, with the objective of making the natural gas network recover more rapidly, and thus the community more resilient. Including bi-directional interdependencies between the natural gas and electric power network, strategic decisions are pursued regarding which distribution pipelines in the gas network should be retrofitted under budget constraints, with the objectives to minimizing the number of people without natural gas in the residential sector and business losses due to the lack of natural gas in non-residential sectors. Monte Carlo Simulation (MCS) is used in order to propagate uncertainties and Probabilistic Seismic Hazard Assessment (PSHA) is adopted in order to capture uncertainties in the seismic hazard with an approach to preserve spatial correlation. A non-dominated sorting genetic algorithm (NSGA-II) approach is utilized to solve the multi-objective optimization problem under study. The results prove the potential of the developed methodology to provide risk-informed decision support, while being able to deal with large-scale, interdependent complex infrastructure considering probabilistic seismic hazard scenarios
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