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Please use this identifier to cite or link to this item: https://dspace.lboro.ac.uk/2134/4845

Title: Phased mission system design optimisation using genetic algorithms
Authors: Astapenko, D.
Bartlett, L.M.
Keywords: Phased missions
Genetic algorithms
Issue Date: 2009
Publisher: © RAMS Consultants
Citation: ASTAPENKO, D. and BARTLETT, L.M., 2009. Phased mission system design optimisation using genetic algorithms. International Journal of Performability Engineering, 5 (4), pp.313-324.
Abstract: A phased mission system represents a system whose performance is divided into consecutive non-overlapping phases. It is important to ensure safety of a phased mission system since the failure of it can have both life threatening and financial consequences. The focus of this paper is to develop an optimisation method to construct an optimal design case for a phased mission system, with the aim of minimising its unreliability and at the same time ensuring optimal usage of available resources throughout all phases. The introduced phased mission optimisation is represented as the constrained single objective problem. Here failure of the overall mission is the objective function and the introduced constraints are employed to determine the optimal use of resources. The implemented optimisation method employs Fault Tree Analysis to represent system performance and Binary Decision Diagrams to quantify each phase failure probability. A single objective Genetic Algorithm has been chosen as the optimisation technique. An Unmanned Aerial Vehicle mission has been selected to demonstrate the methods application. The results and the influence of modifications to the optimisation algorithm are discussed.
Description: This is an article from the serial, International Journal of Performability Engineering [© RAMS Consultants] and it is also available at: http://www.ijpe-online.com/index.html
Version: Accepted for publication
URI: https://dspace.lboro.ac.uk/2134/4845
ISSN: 0973-1318
Appears in Collections:Published Articles (Aeronautical and Automotive Engineering)

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