Using Mathematical Models in Decision Making Methodologies to Find Key Nodes in the Noordin Dark Network
Using Mathematical Models in Decision Making Methodologies to Find Key Nodes in the Noordin Dark Network作者机构：Department of Defense Analysis Naval Postgraduate School Monterey USA
出 版 物：《American Journal of Operations Research》 (美国运筹学期刊（英文）)
年 卷 期：2014年第4卷第4期
页 面：255-267页
学科分类：1002[医学-临床医学] 100214[医学-肿瘤学] 10[医学]
主 题：Social Network Analysis Multi-Attribute Decision Making Analytical Hierarchy Process (AHP) Decision Criterion Weighted Criterion TOPSIS Node Influence Sensitivity Analysis Average Weighted Ranks
摘 要：A Dark Network is a network that cannot be accessed through tradition means. Once uncovered, to any degree, dark network analysis can be accomplished using the SNA software. The output of SNA software includes many measures and metrics. For each of these measures and metric, the output in ORA additionally provides the ability to obtain a rank ordering of the nodes in terms of these measures. We might use this information in decision making concerning best methods to disrupt or deceive a given dark network. In the Noordin Dark network, different nodes were identified as key nodes based upon the metric used. Our goal in this paper is to use methodologies to identify the key players or nodes in a Dark Network in a similar manner as we previously proposed in social networks. We apply two multi-attribute decision making methods, a hybrid AHP & TOPSIS and an average weighted ranks scheme, to analyze these outputs to find the most influential nodes as a function of the decision makers’ inputs. We compare these methods by illustration using the Noordin Dark Network with seventy-nine nodes. We discuss sensitivity analysis that is applied to the criteria weights in order to measure the change in the ranking of the nodes.
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