MultiSQP-GS: a sequential quadratic programming algorithm via gradient sampling for nonsmooth constrained multiobjective optimization

In this paper, we propose a method for solving constrained nonsmooth multiobjective optimization problems which is based on a Sequential Quadratic Programming (SQP) type approach and the Gradient Sampling (GS) technique. We consider the multiobjective problems with noncovex and nonsmooth objective a...

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Veröffentlicht in:	Computational optimization and applications Jg. 89; H. 3; S. 729 - 767
Hauptverfasser:	Rashidi, Mehri, Soleimani-damaneh, Majid
Format:	Journal Article
Sprache:	Englisch
Veröffentlicht:	New York Springer US 01.12.2024
Schlagworte:	Convex and Discrete Geometry Management Science Mathematics Mathematics and Statistics Operations Research Operations Research/Decision Theory Optimization Statistics Gradient Sampling (GS) Nonconvex optimization 49J52 Multiobjective programming 90C29 Nonsmooth optimization 90C26 Exact penalization Sequential Quadratic Programming (SQP) Constrained optimization
ISSN:	0926-6003, 1573-2894
Online-Zugang:	Volltext
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