A conjugate gradient sampling method for nonsmooth optimization

We present an algorithm for minimizing locally Lipschitz functions being continuously differentiable in an open dense subset of R n . The function may be nonsmooth and/or nonconvex. The method makes use of a gradient sampling method along with a conjugate gradient scheme. To find search directions,...

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Veröffentlicht in:	4OR 2020-03, Vol.18 (1), p.73-90
Hauptverfasser:	Mahdavi-Amiri, N., Shaeiri, M.
Format:	Artikel
Sprache:	eng
Schlagworte:	Algorithms Approximation Business and Management Conjugate gradient method Conjugates Industrial and Production Engineering Mathematical analysis Matrix methods Operations research Operations Research/Decision Theory Optimization Queuing theory Research Paper Sampling Sampling methods
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