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Neural Computing and Applications
Erschienen in: Neural Computing and Applications 8/2019

30.01.2018 | Original Article

Sufficiency and duality in interval-valued variational programming

verfasst von: I. Ahmad, Anurag Jayswal, S. Al-Homidan, Jonaki Banerjee

Erschienen in: Neural Computing and Applications | Ausgabe 8/2019

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Abstract

In the present paper, we focus our study on an interval-valued variational problem and derive sufficient optimality conditions by using the notion of invexity. In order to relate the primal interval-valued variational problem and its dual, several duality results, viz., weak, strong and converse duality results are established. Further, the Lagrangian function for the considered interval-valued variational problem is defined and we present some relations between an optimal solution of the considered interval-valued variational problem and a saddle point of the Lagrangian function. In order to illustrate the results proved in the paper, some examples of interval-valued variational problems have been formulated.
Vorheriger Artikel A new and fast correntropy-based method for system identification with exemplifications in low-SNR communications regime
Nächster Artikel An improved TLBO with logarithmic spiral and triangular mutation for global optimization

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Metadaten
Titel
Sufficiency and duality in interval-valued variational programming
verfasst von
I. Ahmad
Anurag Jayswal
S. Al-Homidan
Jonaki Banerjee
Publikationsdatum
30.01.2018
Verlag
Springer London
Erschienen in
Neural Computing and Applications / Ausgabe 8/2019
Print ISSN: 0941-0643
Elektronische ISSN: 1433-3058
DOI
https://doi.org/10.1007/s00521-017-3307-y

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