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Civil-Comp Proceedings
ISSN 1759-3433
CCP: 72
IDENTIFICATION, CONTROL AND OPTIMISATION OF ENGINEERING STRUCTURES
Edited by: G. De Roeck and B.H.V. Topping
Paper III.1

Mixed Discrete and Integer Structural Optimization using Generalized Hopfield Network based Sequential Unconstrained Mimimization Technique with Additional Penalty Strategy

C.J. Shih and Y.C. Yang

Department of Mechanical Engineering, Tamkang University, Tamsui, Taiwan

Full Bibliographic Reference for this paper
C.J. Shih, Y.C. Yang, "Mixed Discrete and Integer Structural Optimization using Generalized Hopfield Network based Sequential Unconstrained Mimimization Technique with Additional Penalty Strategy", in G. De Roeck, B.H.V. Topping, (Editors), "Identification, Control and Optimisation of Engineering Structures", Civil-Comp Press, Edinburgh, UK, pp 73-78, 2000. doi:10.4203/ccp.72.3.1
Abstract
This paper presents and examines a neuron-like framework named the generalized Hopfield network (GHN) that is capable to solve nonlinear optimization problems with mixed discrete, integer and real continuous variables. The sequential unstrained minimization technique (SUMT) was applied to transform a constrained problem to an unconstrained formulation. An additional penalty function for dealing with discrete and integer variables was then imposed on the formulation of SUMT to construct an energy function for formulating the neuron-like dynamical system. The numerical solution process for such a dynamic system is nothing but solving a set of simultaneously first-order ordinary differential equations. The experimental examples showed the presenting strategy is efficient and reliable. The suitable values or the adaptation technique for some parameters in computation was discussed in the paper. The presenting strategy provides another mode of handling die engineering optimization dynamically. This alternative optimization approach also extends the limit of numerical structural engineering optimization.

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