Structural optimization of forest machines with hybridized nonsmooth and global methods

Authors:
P. Auvinen;M. M. Mäkelä;J. Mäkinen
Affiliations:
Department of Mathematical Information Technology, University of Jyväskylä, P.O. Box 35 (Agora), FIN-40351 Jyväskylä, Finland e-mail: makela@mit.jyu.fi, Finland;Department of Mathematical Information Technology, University of Jyväskylä, P.O. Box 35 (Agora), FIN-40351 Jyväskylä, Finland e-mail: makela@mit.jyu.fi, Finland;Department of Mathematical Information Technology, University of Jyväskylä, P.O. Box 35 (Agora), FIN-40351 Jyväskylä, Finland e-mail: makela@mit.jyu.fi, Finland
Venue:
Structural and Multidisciplinary Optimization
Year:
2002

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Abstract

We consider an optimal shape design problem of grapple loaders. Our aim is to minimize the weight of the machine. The durability is taken into account via stress and buckling constraints. Thus we have a nonlinear and nonconvex constrained optimization problem, which, due to the buckling constraints, is also nondifferentiable. The optimization is realized by using the hybridization of a genetic algorithm and a nonsmooth proximal bundle method in order to maintain the advantages of both the methods: reliability and computational efficiency, respectively.