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Tuesday, May 5, 2020 | History

2 edition of Analytical and computational aspects of collaborative optimization found in the catalog.

Analytical and computational aspects of collaborative optimization

Natalia M. Alexandrov

Analytical and computational aspects of collaborative optimization

by Natalia M. Alexandrov

  • 263 Want to read
  • 23 Currently reading

Published by National Aeronautics and Space Administration, Langley Research Center, Available from National Technical Information Service in Hampton, VA, Springfield, VA .
Written in English

    Subjects:
  • Mathematical optimization.,
  • Multidisciplinary design optimization.

  • Edition Notes

    StatementNatalia M. Alexandrov, Robert Michael Lewis.
    SeriesNASA/TM -- 2000-210104, NASA technical memorandum -- 2000-210104.
    ContributionsLewis, Robert Michael., Langley Research Center.
    The Physical Object
    Pagination26 p. :
    Number of Pages26
    ID Numbers
    Open LibraryOL19427962M

    A uniquely pedagogical, insightful, and rigorous treatment of the analytical/geometrical foundations of optimization. This major book provides a comprehensive development of convexity theory, and its rich applications in optimization, including duality, minimax/saddle point theory, Lagrange multipliers, and Lagrangian relaxation/nondifferentiable optimization. It is an excellent supplement to. Properties of the Coupled Factors in MDO and Their Application in Collaborative Optimization,” Analytical and Computational Aspects of Collaborative Optimization for Multidisciplinary Design,” Crossref. Search ADS Steward, D. V., , Systems Analysis and Management: Structure, Strategy, Design, Petrocelli Books, New by:

      Analytical target cascading is a method for design optimization of hierarchical, multilevel systems. A quadratic penalty relaxation of the system consistency constraints is used to ensure subproblem feasibility. A typical nested solution strategy consists of inner and outer loops. In the inner loop, the coupled subproblems are solved iteratively with fixed penalty by:   An Efficient Weighting Update Method to Achieve Acceptable Consistency Deviation in Analytical Target Cascading and Papalambros, P. Y. (Ma ). "An Efficient Weighting Update Method to Achieve Acceptable Consistency Deviation in Analytical Target Cascading." , “Analytical and Computational Aspects of Collaborative Cited by:

    The classic aspects of optimization in power systems, such as optimal power flow, economic dispatch, unit commitment and power quality optimization are covered, as are issues relating to distributed generation sizing, allocation problems, scheduling of renewable resources, energy storage, power reserve based problems, efficient use of smart. Computational Aspects of the Methods Efficient solution of a linear system is largely a function of the proper choice of iterative method. However, to obtain good performance, consideration must also be given to the computational kernels of the method and how efficiently they can be .


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Analytical and computational aspects of collaborative optimization by Natalia M. Alexandrov Download PDF EPUB FB2

Disciplinary optimization in engineering. We examine the analytical and computational properties of one such approach, collaborative optimization.

The resulting system-level optimization problems suffer from inherent computational difficulties due to the bilevel nature of. Collaborative optimization and 6σ design for composite pressure hull of underwater vehicle based on lamination parameters 30 October | Journal of Marine Science and Technology, Vol.

23, No. 3 A multi-fidelity framework to support the design of More-Electric ActuationCited by: Collaborative optimization for ring-stiffened composite pressure hull of underwater vehicle based on lamination parameters International Journal of Naval Architecture and Ocean Engineering, Vol.

9, No. 4Cited by: Download Citation | Analytical and computational aspects of collaborative optimization | Bilevel problem formulations have received considerable attention as an approach to multidisciplinary. ADS Classic is now deprecated.

It will be completely retired in October Please redirect your searches to the new ADS modern form or the classic info can be found on our blog. There are two problems in Collaborative optimization (CO): (1) the local optima arising from the selection of an inappropriate initial point; (2) the low efficiency and accuracy root in.

NASA/TM{{ Analytical and Computational Aspects of Collaborative Optimization () Cached. Download Links [] {{ Analytical and Computational Aspects of Collaborative Optimization}, year = {}} Share. OpenURL. Analytical and computational properties of distributed approaches to MDO.

Analytical and Computational Aspects of Collaborative Optimization for Multidisciplinary Design. Natalia M. Alexandrov and The New Effective MDO Method Based on Collaborative Optimization.

Multi-objective collaborative optimization using linear physical programming with dynamic weight 10 February | Journal of Mechanical Science and Technology, Vol. 30, No. 2 An application of multidisciplinary design optimization to the hydrodynamic performances of Cited by:   Instead of the past mathematical analyses, an intuitive geometric analysis of the collaborative optimization (CO) algorithm is presented in this paper, which reveals some geometric properties of CO and gives a direct geometric interpretation of the reason for the reported computational difficulties in CO.

The analysis shows that if the system-level optimum point at one iteration is outside Cited by: A framework for solving the multiobjective optimization problems in multidisciplinary design environment is advised in this paper.

Based on the collaborative optimization (CO) algorithm, a new system level objective function is advised to minimize relative value between the collaborative objective function and single disciplinary objective by: 2.

Abstract. While multi-agent systems have been successfully applied to combinatorial optimization, very few works concern their applicability to continuous optimization problems.

In this article we propose a framework for modeling a continuous optimization problems as multi-agent system, which we call NDMO, by representing Author: Tom Jorquera, Jean-Pierre Georgé, Marie-Pierre Gleizes, Christine Régis.

Collaborative optimization is described in more detail in [10][11][12][13][14][15][16][17] [18], but consists basically of a bi-level optimization architecture in which individual disciplinary.

Analysis and Enhancement of Collaborative Optimization for Multidisciplinary Design. JiGuan G. Lin ; 2 May | AIAA Journal, Vol. 42, No.

2 Analytical and Computational Aspects of Collaborative Optimization for Multidisciplinary Design. Analytical and computational properties of distributed approaches to MDO. Analytical and Computational Aspects of Collaborative Optimization for Multidisciplinary Design[J]. AIAA Journal. 40(2): [2] Xiang Li, Weiji Li, &KDQJÂDQ / by: 4.

The multiobjective collaborative optimization (MCO) has been widely adopted in concurrent engineering design as a good multiobjective optimization approach provided the problem of optimization results converging often to a local extremum has been taken care : Haiyan Li, Yuanwei Jing, Siying Zhang, Vesna M.

Ojleska, Tatjana D. Kolemisevska, Georgi M. Dimirovs. Multiobjective Collaborative Robust Optimization With Interval Uncertainty and Interdisciplinary Uncertainty Propagation M. Li, M. Analytical and Computational Aspects of Collaborative Optimization for Multidisciplinary Design,” AIAA by: Multidisciplinary Design Optimization (MDO) is an effective and prospective solution to complex engineering systems.

N.M., Lewis, R.M.: Analytical and computational aspects of collaborative optimization for multidisciplinary design. AIAA Jour – R.M.: Analytical and Computational Aspects of Collaborative Optimization. NASA Author: Peng Wang, Bao-Wei Song, Qi-Feng Zhu.

If analysis models are available to represent the consequences of the relevant design decisions, analytical target cascading can be formalized as a hierarchical multilevel optimization problem.

The article demonstrates this complex modeling and solution process Cited by: Collaborative optimization (CO) is a multidisciplinary design optimization (MDO) method with bilevel computational structure, which decomposes the original optimization problem into one system-level problem and several subsystem problems.

The strategy of decomposition in CO is a useful way for solving large engineering design by: 6. Collaborative optimization is a two-level optimization architecture, with discipline-specific optimizations free to specify local designs, and a global optimization that ensures that all of the.This book provides an up-to-date, comprehensive, and rigorous account of nonlinear programming at the first year graduate student level.

It covers descent algorithms for unconstrained and constrained optimization, Lagrange multiplier theory, interior point and augmented Lagrangian methods for linear and nonlinear programs, duality theory, and major aspects of large-scale optimization.Analytical target cascading is a method for design optimization of hierarchical, multilevel systems.

A quadratic penalty relaxation of the system consistency constraints is used to ensure.