Title: System of systems analytic hierarchy and stochastic optimisation design

Authors: Nan Liu; Souran Manoochehri; Chan Yu

Addresses: Micro Financial System Inc., P.O. Box #1094, Hoboken, NJ 07030, USA ' Design & Manufacturing Institute (DMI), Stevens Institute of Technology, 1 Castle Point on Hudson, Hoboken, NJ 07030-3585, USA ' Design & Manufacturing Institute (DMI), Stevens Institute of Technology, 1 Castle Point on Hudson, Hoboken, NJ 07030-3585, USA

Abstract: A formulated methodology of developing the system of systems analytical hierarchy and optimisation flow order is presented. The design problem is modelled as a multi-level hierarchical optimisation problem. The multi-levels such as, super system level, system level and subsystem level are defined. Based on the idea of system of systems, each system performance criteria can be decomposed into several subsystems according to their individual functions. At the super system level, performance objective function is considered by minimising the variances between specified expected values of performance functions and their target values and uncertainty effects caused by global variables. The different levels are linked by the global variables. At the same level, all the subsystems are connected by the linking variables. The local variables only give contributions to each according local subsystem. A specified way to decide cascading flow order for the multi-level system optimisation decision-making problem introduced to improve convergence speed, by considering the sensitivity analysis of linking variables for each element. The formulated method is applied to the selected system of systems examples, such as, the sensor network example. The optimised results based on methods such as genetic algorithm (GA) are provided.

Keywords: complex systems; large-scale systems; multidisciplinary optimisation; probabilistic constraints; conceptual design; decision making; sensitivity analytics; system of systems; analytical hierarchy; stochastic design; optimisation flow order; sensor networks; genetic algorithms.

DOI: 10.1504/IJSSE.2014.064834

International Journal of System of Systems Engineering, 2014 Vol.5 No.2, pp.114 - 124

Available online: 16 Sep 2014 *

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