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Performance Utility-Analysis of Multi-State Systems

Wu, Shaomin, Chan, Ling-Yau (2003) Performance Utility-Analysis of Multi-State Systems. IEEE Transactions on Reliability, 52 (1). pp. 14-21. ISSN 0018-9529. (doi:10.1109/TR.2002.805783) (The full text of this publication is not currently available from this repository. You may be able to access a copy if URLs are provided) (KAR id:31027)

The full text of this publication is not currently available from this repository. You may be able to access a copy if URLs are provided.
Official URL:
http://dx.doi.org/10.1109/TR.2002.805783

Abstract

This paper defines a new utility importance of a state of a Component in multi-state systems. This utility importance overcomes some drawbacks of a well-known importance measure suggested by William S. Griffith (J. Applied Probability, 1980). The relationship between this new utility importance and the Griffith importance is studied and their difference is illustrated with examples. The contribution of an individual component to the performance utility of a multi-state system is discussed. Examples show that a meaningful index for measuring the performance of individual components in a multi-state system can hardly be defined in general, without considering the actual values of the utility levels and the distributions of the component-states in the system. An example illustrates how genetic algorithm, simulated annealing, and tabu search can be used in selecting components and defining the position order of components so that the performance utility of a multi-state system is optimized.

Item Type: Article
DOI/Identification number: 10.1109/TR.2002.805783
Additional information: Unmapped bibliographic data: PY - 2003/// [EPrints field already has value set] AD - Department of Computer Science, University of Bristol, Bristol BS8 1UB, United Kingdom [Field not mapped to EPrints] AD - Dept. of Indust./Mfg. Syst. Eng., University of Hong Kong, Hong Kong, Hong Kong [Field not mapped to EPrints] JA - IEEE Trans Reliab [Field not mapped to EPrints]
Uncontrolled keywords: Multi-state systems, State importance, Utility importance, Genetic algorithms, Probability distributions, Simulated annealing, Vectors, Multi-state systems, Functions
Subjects: H Social Sciences
H Social Sciences > HA Statistics > HA33 Management Science
Divisions: Divisions > Kent Business School - Division > Department of Analytics, Operations and Systems
Depositing User: Shaomin Wu
Date Deposited: 26 Sep 2012 16:25 UTC
Last Modified: 16 Nov 2021 10:08 UTC
Resource URI: https://kar.kent.ac.uk/id/eprint/31027 (The current URI for this page, for reference purposes)

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