Derivative-free methods for mixed-integer nonsmooth constrained optimization

In this paper, mixed-integer nonsmooth constrained optimization problems are considered, where objective/constraint functions are available only as the output of a black-box zeroth-order oracle that does not provide derivative information. A new derivative-free linesearch-based algorithmic framework...

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Bibliographic Details
Published in:	Computational optimization and applications Vol. 82; no. 2; pp. 293 - 327
Main Authors:	Giovannelli, Tommaso, Liuzzi, Giampaolo, Lucidi, Stefano, Rinaldi, Francesco
Format:	Journal Article
Language:	English
Published:	New York Springer US 01.06.2022 Springer Nature B.V
Subjects:	Algorithms Constraints Convex and Discrete Geometry Derivatives Management Science Mathematics Mathematics and Statistics Mixed integer Operations Research Operations Research/Decision Theory Optimization Statistics Variables Nonsmooth optimization 65K05 Mixed-integer nonlinear programming 90C11 90C56 Derivative-free optimization
ISSN:	0926-6003, 1573-2894
Online Access:	Get full text
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