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MINLP and MILP Strategies for Discrete Sizing Structural Optimization Problems

by Omar N. Ghattas, Carnegie Mellon Univ, Pittsburgh, United States,
Ignacio E. Grossmann, Carnegie Mellon Univ, Pittsburgh, United States,



Document Type: Proceeding Paper

Part of: Electronic Computation

Abstract:

We address an important practical problem of optimum structural design in the presence of discrete sizing constraints. In addition, the topology of the structure may vary as well. The problem can be posed as an nonconvex nonlinear discrete optimization problem. We discuss solution strategies, and circumvent the nonconvexities by reformulating the problem as a binary-linear problem. The resulting form of the problem is guaranteed to produce a global optimum. We demonstrate the linear and nonlinear formulations with two numerical examples.

Subject Headings: Structural design | Structural analysis | Numerical analysis | Nonlinear analysis | Linear analysis | Computer programming | Approximation methods

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