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http://hdl.handle.net/10553/76161
Título: | Bi and tri-objective optimization in the deterministic network interdiction problem | Autores/as: | Rocco S, Claudio M. Emmanuel Ramirez-Marquez, Jose Salazar Aponte, Daniel E. |
Clasificación UNESCO: | 3310 tecnología industrial 330411 Diseño de sistemas de calculo |
Palabras clave: | Evolutionary Approach Algorithms Design Models Network, et al. |
Fecha de publicación: | 2010 | Publicación seriada: | Reliability Engineering and System Safety | Resumen: | Solution approaches to the deterministic network interdiction problem have previously been developed for optimizing a single figure-of-merit of the network configuration (i.e. flow that can be transmitted between a source node and a sink node for a fixed network design) under constraints related to limited amount of resources available to interdict network links. These approaches work under the assumption that: (1) nominal capacity of each link is completely reduced when interdicted and (2) there is a single criterion to optimize. This paper presents a newly developed evolutionary algorithm that for the first time allows solving multi-objective optimization models for the design of network interdiction strategies that take into account a variety of figures-of-merit. The algorithm provides an approximation to the optimal Pareto frontier using: (a) techniques in Monte Carlo simulation to generate potential network interdiction strategies, (b) graph theory to analyze strategies' maximum source-sink flow and (c) an evolutionary search that is driven by the probability that a link will belong to the optimal Pareto set. Examples for different sizes of networks and network behavior are used throughout the paper to illustrate and validate the approach. | URI: | http://hdl.handle.net/10553/76161 | ISSN: | 0951-8320 | DOI: | 10.1016/j.ress.2010.03.008 | Fuente: | Reliability Engineering and System Safety [ISSN 0951-8320], v. 95 (8), p. 887-896, (Agosto 2010) |
Colección: | Artículos |
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