Please use this identifier to cite or link to this item: http://hdl.handle.net/10553/76161
Title: Bi and tri-objective optimization in the deterministic network interdiction problem
Authors: Rocco S, Claudio M.
Emmanuel Ramirez-Marquez, Jose
Salazar Aponte, Daniel E.
UNESCO Clasification: 3310 tecnología industrial
330411 Diseño de sistemas de calculo
Keywords: Evolutionary Approach
Algorithms
Design
Models
Network, et al
Issue Date: 2010
Journal: Reliability Engineering and System Safety 
Abstract: 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
Source: Reliability Engineering and System Safety [ISSN 0951-8320], v. 95 (8), p. 887-896, (Agosto 2010)
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