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Autor
Rastogi Sachin (M.J.P. Rohilkhand University, Bareilly, India), Iqbal Akhlad (Aligarh Muslim University, Aligarh, India), Rajan Sanjeev (M.J.P. Rohilkhand University, Bareilly, India)
Tytuł
Optimality Conditions for Preinvex Functions Using Symmetric Derivative
Źródło
Operations Research and Decisions, 2022, vol. 32, no. 4, s. 91-101, bibliogr. 23 poz.
Słowa kluczowe
Optymalizacja, Funkcje, Pochodna
Optimalization, Functions, Derivative
Uwagi
summ.
Abstrakt
As a generalization of convex functions and derivatives, in this paper, the authors study the concept of a symmetric derivative for preinvex functions. Using symmetrical differentiation, they discuss an important characterization for preinvex functions and define symmetrically pseudo-invex and symmetrically quasi-invex functions. They also generalize the first derivative theorem for symmetrically differentiable functions and establish some relationships between symmetrically pseudo-invex and symmetrically quasi-invex functions. They also discuss the Fritz John type optimality conditions for preinvex, symmetrically pseudo-invex and symmetrically quasi-invex functions using symmetrical differentiability. (original abstract)
Dostępne w
Biblioteka Główna Uniwersytetu Ekonomicznego w Krakowie
Biblioteka SGH im. Profesora Andrzeja Grodka
Pełny tekst
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Bibliografia
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Cytowane przez
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ISSN
2081-8858
Język
eng
URI / DOI
http://dx.doi.org/10.37190/ord220406
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