Mixed-integer Non-linear Programming
Approach To Structural Optimization
Author(s)
S. Kravanja
Abstract
The paper presents the Mixed-Integer Non-Linear Programming (MINLP)
approach to structural optimization. MINLP is a combined discrete/continuous
optimization technique, where discrete binary 0-1 variables are defined for
optimization of discrete alternatives and continuous variables for optimization of
parameters. The MINLP optimization is performed through three steps: i.e. the
generation of a mechanical superstructure, the modelling of an MINLP model
formulation and the solution of the defined MINLP problem. As the
discrete/continuous optimization problems are usually non-convex and highly
non-linear, the Modified Outer-Approximation/Equality-Relaxation (OA/ER)
algorithm is applied for the optimization. The accompanied Linked Multilevel
Hierarchical Strategy (LMHS) is developed to accelerate the convergence of the
mentioned algorithm. Two examples are presented at the end of the paper.
Keywords: mixed-integer non-linear programming, MINLP, structural
optimization, structural synthesis.
Keywords
mixed-integer non-linear programming, MINLP, structural
optimization, structural synthesis.
Related Book
Other papers in this volume
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