Evaluation of Multidisciplinary Optimization Approaches for Aircraft Conceptual Design

Perez, Ruben E.; Liu, Hugh H. T.; Behdinan, Kamran

doi:10.2514/6.2004-4537

Cited by 83 publications

(64 citation statements)

References 11 publications

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“…The classification may be used as a starting point for a numerical comparison study of the various formulations. For (discussions on) numerical comparisons, the reader is referred to Balling andSobieszczanski-Sobieski (1995, 1996), Balling and Wilkinson (1997), Alexandrov and Lewis (1999), Perez et al (2004), Yi et al (2008), and the references therein. Since specifying various problem decompositions for a number of coordination approaches is tedious and error prone, a flexible and user-friendly approach is desired for specification of problem partitions, and implementation of coordination methods.…”

Section: Summarizing Remarksmentioning

confidence: 99%

A classification of methods for distributed system optimization based on formulation structure

Tosserams

Etman

Rooda

2009

Struct Multidisc Optim

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This paper presents a classification of formulations for distributed system optimization based on formulation structure. Two main classes are identified: nested formulations and alternating formulations. Nested formulations are bilevel programming problems where optimization subproblems are nested in the functions of a coordinating master problem. Alternating formulations iterate between solving a master problem and disciplinary subproblems in a sequential scheme. Methods included in the former class are collaborative optimization and BLISS2000. The latter class includes concurrent subspace optimization, analytical target cascading, and augmented Lagrangian coordination. Although the distinction between nested and alternating formulations has not been made in earlier comparisons, it plays a crucial role in the theoretical and computational properties of distributed optimization methods. The most prominent general characteristics for each class are discussed in more detail, providing valuable insights for the theoretical analysis and further development of distributed optimization methods.

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Section: Summarizing Remarksmentioning

confidence: 99%

A classification of methods for distributed system optimization based on formulation structure

Tosserams

Etman

Rooda

2009

Struct Multidisc Optim

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“…Numerical and analytical studies indicate that the choice of coordination method has a direct influence on the computational performance with which a problem can be solved (Perez et al 2004;de Wit and van Keulen 2007;Yi et al 2008). Computational frameworks have been developed to facilitate the implementation and testing of coordination methods (see again the introduction section for references).…”

Section: Coordinationmentioning

confidence: 99%

“…See Balling and Sobieszczanski-Sobieski (1996), Sobieszczanski-Sobieski and Haftka (1997), Perez et al (2004), Tosserams et al (2007), Allison et al (2007), de Wit and van Keulen (2007), Yi et al (2008), and Tosserams et al (2009a) for examples of these observations. Experimentation with different system decompositions within the available generic coordination frameworks is not straightforward.…”

Section: Introductionmentioning

confidence: 99%

A specification language for problem partitioning in decomposition-based design optimization

Tosserams

Hofkamp

Etman

et al. 2010

Struct Multidisc Optim

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Decomposition-based design optimization consists of two steps: partitioning of a system design problem into a number of subproblems, and coordination of the design of the decomposed system. Although several generic frameworks for coordination method implementation are available (the second step), generic approaches for specification of the partitioned problem (the first step) are rare. Available specification methods are often based on matrix or graph representations of the entire system. For larger systems these representations become intractable due to the large number of design variables and functions. This article presents a new linguistic approach for specification of partitioned problems in decomposition-based design optimization. With the elements of the proposed specification language, called (the Greek letter "Psi"), a designer can define subproblems, and assemble these into larger systems in a bottom-up fashion. The assembly process allows the system designer to control the complexity and tractability of the problem partitioning task. To facilitate coupling to generic coordination frameworks, a compiler has been developed for that generates an interchange file in the INI format. This INI-definition of the partitioned problem can easily be interpreted by programs written in other languages. The flexibility provided by the language and

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“…Typically the selection of an MDO method is done in an ad hoc manner, since few benchmarking studies are available to make an informed decision (Alexandrov and Kodiyalam 1998). Results from various studies have shown that the performance of a method can be dependent on its implementation, the characteristics of the problem being solved, and the optimizer employed (Alexandrov and Kodiyalam 1998;Brown and Olds 2006;Perez et al 2004). Furthermore, for some problems, specific methods may either fail to return an optimum, or may not be suited to implementation (Brown and Olds 2006).…”

Section: Introductionmentioning

confidence: 99%

Benchmarking multidisciplinary design optimization algorithms

2009

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A comparison of algorithms for multidisciplinary design optimization (MDO) is performed with the aid of a new software framework. This framework, pyMDO, was developed in Python and is shown to be an excellent platform for comparing the performance of the various MDO methods. pyMDO eliminates the need for reformulation when solving a given problem using different MDO methods: once a problem has been described, it can automatically be cast into any method. In addition, the modular design of pyMDO allows rapid development and benchmarking of new methods. Results generated from this study provide a strong foundation for identifying the performance trends of various methods with several types of problems.

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Evaluation of Multidisciplinary Optimization Approaches for Aircraft Conceptual Design

Cited by 83 publications

References 11 publications

A classification of methods for distributed system optimization based on formulation structure

A classification of methods for distributed system optimization based on formulation structure

A specification language for problem partitioning in decomposition-based design optimization

Benchmarking multidisciplinary design optimization algorithms

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