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Coevolutionary architecture for distributed optimization of complex coupled systems

Coevolutionary architecture for distributed optimization of complex coupled systems
Coevolutionary architecture for distributed optimization of complex coupled systems
A coevolutionary architecture for distributed optimization of complex coupled systems is presented. This architecture is inspired by the phenomena of coevolutionary adaptation occurring in ecological systems. The focus of this research is to develop flexible design architectures for addressing the organizational and computational challenges involved in optimization of large-scale multidisciplinary systems. In the proposed design architecture the optimization procedure ismodeled as the process of coadaptationbetween sympatric species in an ecosystem. Each species is entrusted with the task of improving subdomain specifc objectives and the satisfaction of subdomain constraints. Coupling compatibility constraints are accommodated via implicit generalized Jacobi iteration, which enables the application of the proposed architecture to systems with arbitrary coupling bandwidth between the disciplines, without an increase in the problemsize. A domain decomposition approach is presented for distributed structural optimization to construct a class of test problems. Numerical studies are presented to demonstrate that convergence to an optimal solution satisfying the subdomain and coupling compatibility constraints can be readily achieved.
0001-1452
1434-1443
Nair, Prasanth B.
d4d61705-bc97-478e-9e11-bcef6683afe7
Keane, Andy J.
26d7fa33-5415-4910-89d8-fb3620413def
Nair, Prasanth B.
d4d61705-bc97-478e-9e11-bcef6683afe7
Keane, Andy J.
26d7fa33-5415-4910-89d8-fb3620413def

Nair, Prasanth B. and Keane, Andy J. (2002) Coevolutionary architecture for distributed optimization of complex coupled systems. AIAA Journal, 40 (7), 1434-1443.

Record type: Article

Abstract

A coevolutionary architecture for distributed optimization of complex coupled systems is presented. This architecture is inspired by the phenomena of coevolutionary adaptation occurring in ecological systems. The focus of this research is to develop flexible design architectures for addressing the organizational and computational challenges involved in optimization of large-scale multidisciplinary systems. In the proposed design architecture the optimization procedure ismodeled as the process of coadaptationbetween sympatric species in an ecosystem. Each species is entrusted with the task of improving subdomain specifc objectives and the satisfaction of subdomain constraints. Coupling compatibility constraints are accommodated via implicit generalized Jacobi iteration, which enables the application of the proposed architecture to systems with arbitrary coupling bandwidth between the disciplines, without an increase in the problemsize. A domain decomposition approach is presented for distributed structural optimization to construct a class of test problems. Numerical studies are presented to demonstrate that convergence to an optimal solution satisfying the subdomain and coupling compatibility constraints can be readily achieved.

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Published date: 2002

Identifiers

Local EPrints ID: 22052
URI: http://eprints.soton.ac.uk/id/eprint/22052
ISSN: 0001-1452
PURE UUID: 858a9f9a-ef92-46f6-bb4f-019c019f894d

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Date deposited: 20 Mar 2006
Last modified: 15 Jul 2019 19:23

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Contributors

Author: Prasanth B. Nair
Author: Andy J. Keane

University divisions

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