Convergence Criteria for Hierarchical Overlapping Coordination of Linearly Constrained Convex Design Problems

  • Authors:

  • Hyungju Park;Nestor Michelena;Devadatta Kulkarni;Panos Papalambros

  • Affiliations:

  • Department of Mathematics and Statistics, Oakland University, Rochester, MI 48309. park@oakland.edu;Department of Mechanical Engineering, University of Michigan, Ann Arbor, MI 48109. nestorm@umich.edu;Department of Mathematics and Statistics, Oakland University, Rochester, MI 48309. kulkarni@oakland.edu;Department of Mechanical Engineering, University of Michigan, Ann Arbor, MI 48109. pyp@umich.edu

  • Venue:
  • Computational Optimization and Applications
  • Year:
  • 2001

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Abstract

Decomposition of multidisciplinary engineering system design problems into smaller subproblems is desirable because it enhances robustness and understanding of the numerical results. Moreover, subproblems can be solved in parallel using the optimization technique most suitable for the underlying mathematical form of the subproblem. Hierarchical overlapping coordination (HOC) is an interesting strategy for solving decomposed problems. It simultaneously uses two or more design problem decompositions, each of them associated with different partitions of the design variables and constraints. Coordination is achieved by the exchange of information between decompositions. This article presents the HOC algorithm and several new sufficient conditions for convergence of the algorithm to the optimum in the case of convex problems with linear constraints. One of these equivalent conditions involves the rank of the constraint matrix that is computationally efficient to verify. Computational results obtained by applying the HOC algorithm to quadratic programming problems of various sizes are included for illustration.