Abstract
This work is concerned with differentiable constrained vector optimization problems. It focus on the intrinsic connection between positive linearly dependent gradient sets and the distinct notions of regularity that come to play in this context. The main aspect of this contribution is the development of regularity conditions, based on the positive linear dependence or independence of gradient sets, for problems with general nonlinear constraints, without any convexity hypothesis. Being easy to verify, these conditions might be useful to define termination criteria in the development of algorithms.
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Communicated by F. Giannessi.
This work was supported by Fundación Antorchas, Grant 13900/4; by Southern National University, Grant UNS 24/L069; by Comahue National University, Grant E060/04; by CNPq-Brazil (Grants 302412/2004-2, 473586/2005-5 and 303465/2007-7) and by FAPESP-Brazil (06/53768-0).
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Maciel, M.C., Santos, S.A. & Sottosanto, G.N. Regularity Conditions in Differentiable Vector Optimization Revisited. J Optim Theory Appl 142, 385–398 (2009). https://doi.org/10.1007/s10957-009-9519-2
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DOI: https://doi.org/10.1007/s10957-009-9519-2