An algorithm for solving the system-level problem in multilevel optimization
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An algorithm for solving the system-level problem in multilevel optimization

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Published by National Aeronautics and Space Administration, National Technical Information Service, distributor in [Washington, DC, Springfield, Va .
Written in English


  • Algorithms.,
  • Computer aided design.,
  • Design analysis.,
  • Optimization.

Book details:

Edition Notes

Other titlesAlgorithm for solving the system level problem in multilevel optimization.
StatementR.J. Balling, J. Sobieszczanski-Sobieski.
SeriesICASE report -- no. 94-96., NASA contractor report -- NASA CR-195015.
ContributionsSobieszczanski-Sobieski, Jaroslaw., United States. National Aeronautics and Space Administration.
The Physical Object
Pagination1 v.
ID Numbers
Open LibraryOL15412000M

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BibTeX @MISC{Bailing94analgorithm, author = {R. J. Bailing and J. Sobieszczanski-sobieski and R. J. Balling and J. Sobieszezanski-sobieski}, title = {AN ALGORITHM FOR SOLVING THE SYSTEM-LEVEL PROBLEM IN MULTILEVEL OPTIMIZATION*}, year = {}}. An algorithm for solving the system-level problem in multilevel optimization. Abstract. A multilevel optimization approach which is applicable to nonhierarchic coupled systems is presented. The approach includes a general treatment of design (or behavior) constraints and coupling constraints at the discipline level through the use of norms Author: J. Sobieszczanski-Sobieski and R. J. Balling.   This updating process of the solution continues until a stopping criterion is met. Bilevel and trilevel optimization problems are used to show how the algorithm works. From the simulation result on the two problems, it is shown that it is promising to uses the proposed metaheuristic algorithm in solving multilevel optimization by: We provide a more complete view of line search multilevel algorithm, and in particular, we connect the general framework of the multilevel algorithm with classical optimization algorithms, such as variable metric methods and block-coordinate type methods. We also make a connection with the algorithm stochastic variance reduced gradient (SVRG) [20].

propose an optimization-based multilevel algorithm for efficiently solving a class of selective segmentation models. It also applies to the solution of global segmentation models. In a level-set function formulation, our first variant of the proposed multilevel algorithm has the expected optimal O(NlogN) efficiency for an image of size n n. A novel approach is provided for problems of factorization and decomposition of logic functions, which are an important part of multilevel logic optimization. The key concept is to formulate these.   A multi-level solution method is presented for multi-objective optimization of large-scale systems associated with the hierarchical structure of decision-making. The method, consisting of a multi-level problem formulation and an interactive algorithm, has distinct advantages in handling the difficulties which are often experienced in engineering. Second, available algorithms for solving a problem exactly can be unacceptably slow because of the problem’s intrinsic complexity. This happens, in particular, for many problems involving a very large number of choices; you will see examples of such difficult problems in Chapters 3, 11, and

  The multi-level network optimization (MLNO) problem treated here was introduced recently, and integrates into the same model discrete location, topological network design, and dimensioning aspects.A multi-level network is illustrated in Fig. MLNO problem is defined on a multi-weighted digraph D =(N,A) where N is the set of nodes and A is the set of arcs. Collaborative Optimization of Systems Involving Discrete Design at the Discipline Level R. J. Balling, An Algorithm for Solving the System-Level Problem in Multilevel Optimization,” Two Alternative Ways for Solving the Coordination Problem in Multilevel Optimization,”Cited by: Two alternative ways for solving the coordination problem in. In this book we are primarily interested in optimization algorithms, as op-posed to “modeling,” i.e., the formulation of real-world problems as math-ematical optimization problems, or “theory,” i.e., conditions for strong du-ality, optimality conditions, etc. In our treatment, we will mostly focus on. Multilevel redundancy allocation is an especially powerful approach for improving the system reliability of such hierarchical configurations, and system optimization problems that take advantage.