An approximate subgradient algorithm for unconstrained nonsmooth, nonconvex optimization

Adil Bagirov () and Asef Ganjehlou ()

Mathematical Methods of Operations Research, 2008, vol. 67, issue 2, 187-206

Abstract: In this paper a new algorithm for minimizing locally Lipschitz functions is developed. Descent directions in this algorithm are computed by solving a system of linear inequalities. The convergence of the algorithm is proved for quasidifferentiable semismooth functions. We present the results of numerical experiments with both regular and nonregular objective functions. We also compare the proposed algorithm with two different versions of the subgradient method using the results of numerical experiments. These results demonstrate the superiority of the proposed algorithm over the subgradient method. Copyright Springer-Verlag 2008

Keywords: Nonsmooth optimization; Subdifferential; Semismooth functions; Quasidifferentiable functions; 65K05; 90C25 (search for similar items in EconPapers)
Date: 2008
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Citations: View citations in EconPapers (2)

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DOI: 10.1007/s00186-007-0186-5

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