5,755 research outputs found

    Multi-criteria analysis: a manual

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    Feasibility study of an Integrated Program for Aerospace-vehicle Design (IPAD) system. Volume 2: Characterization of the IPAD system, phase 1, task 1

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    The aircraft design process is discussed along with the degree of participation of the various engineering disciplines considered in this feasibility study

    Evaluating Decision Trees under Different Criteria

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    Based on our earlier results in decision theory, we demonstrate how decision trees can be integrated into a general framework for analysing decision situations with respect to different criteria, and suggest an evaluation rule taking into account all strategies, criteria, probabilities and utilities involved in the situations under consideration. A significant property of the framework is that it admits the representation of imprecise information at all stages. This information is modelled in sets of measures constrained by interval estimates. The strategies are then evaluated relative to different decision rules, e.g., a set of generalisations of the principle of admissibility. Decision situations are evaluated using fast algorithms developed particularly for solving these kinds of problems. The presented framework has been developed and used within a large-scale evaluation project at the Swedish National Rail Administration

    Finding a Collective Set of Items: From Proportional Multirepresentation to Group Recommendation

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    We consider the following problem: There is a set of items (e.g., movies) and a group of agents (e.g., passengers on a plane); each agent has some intrinsic utility for each of the items. Our goal is to pick a set of KK items that maximize the total derived utility of all the agents (i.e., in our example we are to pick KK movies that we put on the plane's entertainment system). However, the actual utility that an agent derives from a given item is only a fraction of its intrinsic one, and this fraction depends on how the agent ranks the item among the chosen, available, ones. We provide a formal specification of the model and provide concrete examples and settings where it is applicable. We show that the problem is hard in general, but we show a number of tractability results for its natural special cases

    Aggregating Centrality Rankings: A Novel Approach to Detect Critical Infrastructure Vulnerabilities

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    Assessing critical infrastructure vulnerabilities is paramount to arrange efficient plans for their protection. Critical infrastructures are network-based systems hence, they are composed of nodes and edges. The literature shows that node criticality, which is the focus of this paper, can be addressed from different metric-based perspectives (e.g., degree, maximal flow, shortest path). However, each metric provides a specific insight while neglecting others. This paper attempts to overcome this pitfall through a methodology based on ranking aggregation. Specifically, we consider several numerical topological descriptors of the nodes’ importance (e.g., degree, betweenness, closeness, etc.) and we convert such descriptors into ratio matrices; then, we extend the Analytic Hierarchy Process problem to the case of multiple ratio matrices and we resort to a Logarithmic Least Squares formulation to identify an aggregated metric that represents a good tradeoff among the different topological descriptors. The procedure is validated considering the Central London Tube network as a case study

    Spare Parts Management for Nuclear Power Generation Facilities

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    With deregulation, utilities in the power sector face a much more urgent imperative to emphasize cost efficiencies as compared to the days of regulation. One major opportunity for cost savings is through reductions in spare parts inventory. Most utilities are accustomed to carrying large volumes of expensive, relatively slow-moving units because of a high degree of risk-averseness. This attitude towards risk is rooted in the days of regulation. Under regulation, companies recovered capital inventory costs by incorporating them into the base rate charged to its customers. In a deregulated environment, cost recovery is no longer guaranteed. Companies must therefore reexamine their risk profile and develop policies for spare parts inventory that are appropriate for a competitive business environment.This research studies the spare parts inventory management problem in the context of electric utilities, with a focus on nuclear power. It addresses three issues related to this problem: criticality, risk, and policy. With respect to criticality and risk, a methodology is presented that incorporates the use of influence diagrams and the Analytic Hierarchy Process (AHP). A new method is developed for group aggregation in the AHP when Saaty and Vargas' (2007) dispersion test fails and decision makers are unwilling or unable to revise their judgments. With respect to policy, a quantitative model that ranks the importance of keeping a part in inventory and recommends a corresponding stocking policy through the use of numerical simulation is developed. This methodology and its corresponding models will enable utilities that have transitioned from a regulated to a deregulated environment become more competitive in their operations while maintaining safety and reliability standards. Furthermore, the methodology developed is general enough so that other utility plants, especially those in the nuclear sector, will be able to use this approach. In addition to regulated utilities, other industries, such as aerospace and the military, can also benefit from extensions to these models, as risk profiles and subsequent policies can be adjusted to align with the business environment in which each industry or company operates
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