This paper describes two approaches that allow decomposition of structural design problems that enable structural design optimization to be performed on systems that are often seen as too large or complex to address in a single optimization. The COMPOSE method is shown to enable optimization of many tightly coupled subsystems despite the usual problem of non-convergence when a subsystem is repeatedly removed and optimized under the previously prevailing boundary conditions, then reinserted into the entire system model, which subsequently causes the boundary conditions experienced by the subsystem to change. Use of COMPOSE may allow reducing the number of whole-system evaluations necessary for component design from hundreds or thousands to fewer than ten, while still exploring the component design space extensively.Asecond approach, collaborative independent agents, is shown to address problems that have both large design spaces and time-intensive analyses, rendering them intractable to traditional methods. In an example problem, a set of loosely coupled optimization agents is shown to reduce dramatically the computing time needed to find good solutions to such problems. The savings result from the continuing transfer of results from rapid, low-refinement, less accurate search to agents that search at the full level of refinement and accuracy demanded of a solution of the problem, essentially providing them guidance as to what portions of the design space are likely to be worth searching in greater detail.
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References
Averill RC, Eby D and Goodman ED (2001) How well can it take a hit? – An advanced automated optimization technique can help designers develop crashworthy structures. ASME Mechanical Engineering Design, March, pp. 26–28.
Averill RC, Punch WF, Goodman ED, Lin S-C, Yip YC, Ding Y (1995) Genetic algorithm-based design of energy-absorbing laminated composite beams. Proc. ASME Design Eng. Tech. Conf ., Vol. 1, Boston, pp. 89–96.
Chapman CD, K. Saitou K and Jakiela MJ (1993) Genetic algorithms as an approach to configuration and topology design. Proc. 1993 ASME Design Automation Conference, Albuquerque, New Mex., Sept.
Daratech Research Staff (2002) Process Integration, Design Optimization Emerging as New Solution Category.
Eby D, Averill RC, Goodman, ED and Punch W (1999) The optimization of flywheels using an injection island genetic algorithm. Evolutionary Design by Computers, P. Bentley, ed., Morgan Kaufmann, San Francisco, pp. 167–190.
Eby D, Averill RC, Punch WF, Mathews O, and Goodman ED (1997) An island injection GA for flywheel design optimization. Proc. EUFIT ’97, Aachen, Germany, pp. 687–691.
Eby D, Averill RC, Punch WF and Goodman E (1998) Evaluation of injection island GA performance on flywheel design optimization. Adaptive Computing in Design and Manufacture, I. C. Parmee, ed., Springer, Berlin, pp. 121–136.
Haftka RT (1984) An Improved Computational Approach for Multilevel Optimum Design. J. Structural Mechanics, Vol. 12, pp. 245–261.
Leung M and Nevill GE, Jr. (1994) Genetic algorithms for preliminary 2-D structural design. Proc. 35th AIAA/ASME/AHS SDM Conf ., Hilton Head, SC, April 18–20.
LeRiche R and Haftka RT (1993) Optimization of laminate stacking sequence for buckling load maximization by genetic algorithm. AIAA Journal, 31, pp. 951–956.
Lin S-C, Punch WF and Goodman ED (1994) Coarse-grain parallel genetic algorithms: categorization and analysis. Proc. IEEE Symposium on Parallel and Distributed Processing, pp.27–36.
Malott B, Averill RC, Goodman ED, Ding Y, and Punch WF (1996) Use of genetic algorithms for optimal design of laminated composite sandwich panels with bending-twisting coupling. AIAA/ASME/ASCE/AHS/ASC 37th Structures, Structural Dynamics and Materials Conf ., Salt Lake City, Utah.
Nagendra S, Haftka RT, and Gurdal Z (1992) Stacking sequence optimization of simply supported laminates with stability and strain constraints. AIAA Journal, 30, pp. 2132–2137.
Nagendra S, Haftka RT, and Gurdal Z (1993) Design of blade stiffened composite panels by a genetic algorithm approach. Proc. 34th AIAA/ASME/AHS SDM Conference, La Jolla, CA, April 19–22, pp. 2418–2436.
Papadrakakis M and Tsompanakis Y (1999) Domain decomposition methods for parallel solution of shape sensitivity analysis problems Int. J. Num. Meth. Eng., Vol. 44, pp. 281–303.
Red Cedar Technology, proprietary internal report, 2001.
Sandgren E, Jensen E, and Welton JW (1990) Topological design of structural components using genetic optimization methods. Sensitivity Analysis and Optimization with Numerical Methods, Saigal S and Mukherjee S, eds, AMD-Vol. 115, ASME, pp. 31–43.
Sobieszczanski-Sobieski J, Altus TD, Phillips M and Sandusky R (2003) Bilevel integrated system synthesis for concurrent and distributed processing. AIAA Journal, Vol. 41, pp. 1996–2003.
Sobieszczanski-Sobieski J, James BB and Dovi RR (1985) Structural optimization by multilevel decomposition. AIAA Journal, Vol. 23, No. 11, pp. 1775–1782.
Sobieszczanski-Sobieski J, James BB and Riley MF (1987) Structural sizing by generalized, multilevel optimization. AIAA Journal, Vol. 25, No. 1, pp. 139–145.
Soto CA and Diaz AR (1993) Optimum layout and shape of plate structures using homogenization. Topology Design of Structures, Bendsoe MP and Mota Soares CA, eds., pp. 407–420.
Suzuki K and Kikuchi N (1990) Shape and topology optimization by a homogenization method. Sensitivity Analysis and Optimization with Numerical Methods, AMD-Vol. 115, ASME, pp. 15–30.
Suzuki K and Kikuchi N (1991) A homogenization method for shape and topology optimization. Comp. Meth. A
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Goodman, E.D., Averill, R.C., Sidhu, R. (2008). Multi-Level Decomposition for Tractability in Structural Design Optimization. In: Yu, T., Davis, L., Baydar, C., Roy, R. (eds) Evolutionary Computation in Practice. Studies in Computational Intelligence, vol 88. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-540-75771-9_3
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