23 research outputs found

    Modern Homotopy Methods in Optimization

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    Probability-one homotopy methods are a class of algorithms for solving nonlinear systems of equations that are accurate, robust, and converge from an arbitrary starting point almost surely. These new techniques have been successfully applied to solve Brouwer faced point problems, polynomial systems of equations, and discretizations of nonlinear two-point boundary value problems based on shooting, finite differences, collocation, and finite elements. This paper summarizes the theory of globally convergent homotopy algorithms for unconstrained and constrained optimization, and gives some examples of actual application of homotopy techniques to engineering optimization problems

    Multi-Objective Control-Structures Optimization Via Homotopy Methods

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    A recently developed active set algorithm for tracking parametrized optima is adapted to multi-objective optimization. The algorithm traces a path of Kuhn-Tucker points using homotopy curve tracking techniques, and is based on identifying and maintaining the set of active constraints. Second order necessary optimality conditions are used to determine nonoptimal stationary points on the path. In the bi-objective optimization case the algoritm is used to trace the curve efficient solutions (Pareto optima). As an example, the algorithm is applied to the simultaneous minimization of the weight and control force of a ten-bar truss with two collocated sensors and actuators, with some interesting results

    Tracing the Efficient Curve for Multi-objective Control-Structure Optimization

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    A recently developed active set algorithm for tracing parametrized optima is adapted to multi-objective optimization. The algorithm traces a path of Kuhn-Tucker points using homotopy curve tracking techniques, and is based on identifying and maintaining the set of active constraints. Second order necessary optimality conditions are used to determine nonoptimal stationary points on the path. In the bi-objective optimization case the algorithm is used to trace the curve of efficient solutions (Pareto optima). As an example, the algorithm is applied to the simultaneous minimization of the weight and control force of a ten-bar truss with two collocated sensors and actuators, with some interesting results

    An Active Set Algorithm for Tracing Parametrized Optima

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    Optimization problems often depend on parameters that define constraints or objective functions. It is often necessary to know the effect of a change in a parameter on the optimum solution. An algorithm is presented here for tracking paths of optimal solutions of inequality constrained nonlinear programming problems as a function of a parameter. The proposed algorithm employs homotopy zero-curve tracing tecnniques to track segments where the set of active constraints is unchanged. The transition between segments is handled by considering all possible sets of active constraints and eliminating nonoptimal ones based on the signs of the Lagrange multipliers and the derivatives of the optimal solutions with respect to the parameter

    Quantifying Effects of Voids in Woven Ceramic Matrix Composites

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    Randomness in woven ceramic matrix composite architecture has been found to cause large variability in stiffness and strength. The inherent voids are an aspect of the architecture that may cause a significant portion of the variability. A study is undertaken to investigate the effects of many voids of random sizes and distributions. Response surface approximations were formulated based on void parameters such as area and length fractions to provide an estimate of the effective stiffness. Obtaining quantitative relationships between the properties of the voids and their effects on stiffness of ceramic matrix composites are of ultimate interest, but the exploratory study presented here starts by first modeling the effects of voids on an isotropic material. Several cases with varying void parameters were modeled which resulted in a large amount of variability of the transverse stiffness and out-of-plane shear stiffness. An investigation into a physical explanation for the stiffness degradation led to the observation that the voids need to be treated as an entity that reduces load bearing capabilities in a space larger than what the void directly occupies through a corrected length fraction or area fraction. This provides explanation as to why void volume fraction is not the only important factor to consider when computing loss of stiffness

    Effects of Microstructural Variability on Thermo-Mechanical Properties of a Woven Ceramic Matrix Composite

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    The objectives of this paper include identifying important architectural parameters that describe the SiC/SiC five-harness satin weave composite and characterizing the statistical distributions and correlations of those parameters from photomicrographs of various cross sections. In addition, realistic artificial cross sections of a 2D representative volume element (RVE) are generated reflecting the variability found in the photomicrographs, which are used to determine the effects of architectural variability on the thermo-mechanical properties. Lastly, preliminary information is obtained on the sensitivity of thermo-mechanical properties to architectural variations. Finite element analysis is used in combination with a response surface and it is shown that the present method is effective in determining the effects of architectural variability on thermo-mechanical properties

    Genetic Algorithms with Local Improvement for Composite Laminate Design

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    This paper describes the application of a genetic algorithm to the stacking sequence optimization of a composite laminate plate for buckling load maximization. Two approaches for reducing the number of analyses are required by the genetic algorithm are described. First, a binary tree is used to store designs, affording an efficient way to retrieve them and thereby avoid repeated analyses of designs that appeared in previous generations. Second, a local improvements scheme based on approximations in terms of lamination parameters is introduced. Two lamination parameters are sufficient to define the flexural stiffness and hence the buckling load of a balanced, symmetrically laminated plate. Results were obtained for rectangular graphite-epoxy plates under biaxial in-plane loading. The proposed improvements are shown to reduce significantly the number of analyses required for the genetic optimization

    Design of Laminated Plates for Maximum Buckling Load

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    The buckling load of laminated plates having midplane symmetry is maximized for a given total thickness. The thicknesses of the layers are taken as the design variables. Buckling analysis is carried out using the finite element method. The optimality equations are solved by a homotopy method which permits tracing optima as a function of total thickness. It is shown that for any design with a given stacking sequence of ply orientations, there exists a design associated with any other stacking sequence which possesses the same bending stiffness matrix and same total thickness. Hence, from the optimum design for a given stacking sequence, one can directly determine the optimum design for any rearrangement of the ply orientations, and the optimum buckling load is independent of the stacking sequence

    Tracking Structural Optima as a Function of Available Resources by a Homotopy Method

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    Optimization problems are typically solved by starting with an initial estimate and proceeding iteratively to improve it until the optimum is found. The design points along the path from the initial estimate to the optimum are usually of no value. The present work proposes a strategy for tracing a path of optimum solutions parameterized by the amount of available resources. The paper specifically treats the optimum design of a structure to maximize its buckling load. Equations for the optimum path are obtained using Lagrange multipliers, and solved by a homotopy method. The solution path has several branches due to changes in the active constraint set and transitions from unimodal to bimodal solutions. The Lagrange multipliers and second-order optimality conditions are used to detect branching points and to switch to the optimum solution path. The procedure is applied to the design of a foundation which supports a column for maximum buckling load. Using the total available foundation stiffness as a homotopy parameter, a set of optimum foundation designs is obtained

    Analysis of a Nonhierarchical Decomposition Algorithm

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    Large scale optimization problems are tractable only if they are somehow decomposed. Hierarchical decompositions are inappropriate for some types of problems and do not parallelize well. Sobieszczanski-Sobieski has proposed a nonhierarchical decomposition strategy for nonlinear constrained optimization that is naturally parallel. Despite some successes on engineering problems, the algorithm as originally proposed fails on simple two dimensional quadratic programs. This paper carefully analyzes the algorithm for quadratic programs, and suggests a number of modifications to improve its robustness
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