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On the coordination of multidisciplinary design optimization using expert systems

On the coordination of multidisciplinary design optimization using expert systems
On the coordination of multidisciplinary design optimization using expert systems
Multidisciplinary Design Optimization (MDO) of complex systems in the enterprise is typically broken down along domain specialist lines with associated expertise, tools, method and process. This paper investigates an approach to MDO that exploits heuristic control of the bounds of the common design variables across the domains of a decomposed problem. By bringing the common design variable vector to a single point in the design space, in the context of internally consistent and multiple discipline feasible state variables (and consistently resolved local design vectors), the MDO problem is solved. We present a system level management system in which an expert system is used to coordinate the activities of the domain level optimizers. Motivated by move limit and trust region algorithms a rule base has been developed to manage the bounds on the common design variable vector, control the exchange and relaxation of state coupling variables and control the specification of the domain level optimization problems. Through application of the rule base across a couple of representative MDO problems assembled from the literature the viability and performance of the method are discussed.
0001-1452
1778-1807
Price, Andrew R.
b020e5b3-c608-4377-af0b-f97cd7ff64dd
Keane, Andy J.
26d7fa33-5415-4910-89d8-fb3620413def
Holden, Carren M.E.
411ab81a-6161-4eef-9d23-8ffc8972b572
Price, Andrew R.
b020e5b3-c608-4377-af0b-f97cd7ff64dd
Keane, Andy J.
26d7fa33-5415-4910-89d8-fb3620413def
Holden, Carren M.E.
411ab81a-6161-4eef-9d23-8ffc8972b572

Price, Andrew R., Keane, Andy J. and Holden, Carren M.E. (2011) On the coordination of multidisciplinary design optimization using expert systems. AIAA Journal, 49 (8), 1778-1807. (doi:10.2514/1.J050928).

Record type: Article

Abstract

Multidisciplinary Design Optimization (MDO) of complex systems in the enterprise is typically broken down along domain specialist lines with associated expertise, tools, method and process. This paper investigates an approach to MDO that exploits heuristic control of the bounds of the common design variables across the domains of a decomposed problem. By bringing the common design variable vector to a single point in the design space, in the context of internally consistent and multiple discipline feasible state variables (and consistently resolved local design vectors), the MDO problem is solved. We present a system level management system in which an expert system is used to coordinate the activities of the domain level optimizers. Motivated by move limit and trust region algorithms a rule base has been developed to manage the bounds on the common design variable vector, control the exchange and relaxation of state coupling variables and control the specification of the domain level optimization problems. Through application of the rule base across a couple of representative MDO problems assembled from the literature the viability and performance of the method are discussed.

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More information

Submitted date: 16 October 2009
Accepted/In Press date: 19 February 2010
Published date: 20 August 2011
Venue - Dates: Learning and Intelligent Optimization - LION4 2010, Venice, Italy, 2010-02-19

Identifiers

Local EPrints ID: 150245
URI: http://eprints.soton.ac.uk/id/eprint/150245
ISSN: 0001-1452
PURE UUID: d84c801e-5ba5-4741-88ee-312ae182eb1c
ORCID for Andy J. Keane: ORCID iD orcid.org/0000-0001-7993-1569

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Date deposited: 26 Oct 2011 16:12
Last modified: 14 Mar 2024 02:39

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Contributors

Author: Andrew R. Price
Author: Andy J. Keane ORCID iD
Author: Carren M.E. Holden

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