Shashi Kant Mishra

Prof. Shashi Kant Mishra

Banaras Hindu University, Varanasi
orcid

Research Focus & Metrics

Academic Career Length

20Years (2007-Present)

(Calculated once Scilit publication data is synced: current year − year of first publication + 1)

Representative Publications

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8 February 2016 in Journal of Optimization Theory and Applications
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Journal Article
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YPYogendra Pandey
Yogendra Pandey
SMShashi Kant Mishra
Shashi Kant Mishra

30 September 2010 in Optimization Letters
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Journal Article
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SMShashi Kant Mishra
Shashi Kant Mishra
MJM. Jaiswal
M. Jaiswal
LALe Thi Hoai An
Le Thi Hoai An


14 November 2017 in Journal of Inequalities and Applications
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Journal Article
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Sy-Ming GuuSy-Ming Guu
Sy-Ming Guu
YSYadvendra Singh
Yadvendra Singh
SMShashi Kant Mishra
Shashi Kant Mishra
In this paper, we consider a nonsmooth multiobjective semi-infinite programming problem with vanishing constraints (MOSIPVC). We introduce stationary conditions for the MOSIPVCs and establish the strong Karush-Kuhn-Tucker type sufficient optimality conditions for the MOSIPVC under generalized convexity assumptions.


17 April 2020 in Mathematics
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Journal Article
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Kin Keung LaiKin Keung Lai
Kin Keung Lai
SMShashi Kant Mishra
Shashi Kant Mishra
BRBhagwat Ram
Bhagwat Ram
A parameter-free optimization technique is applied in Quasi-Newton’s method for solving unconstrained multiobjective optimization problems. The components of the Hessian matrix are constructed using q-derivative, which is positive definite at every iteration. The step-length is computed by an Armijo-like rule which is responsible to escape the point from local minimum to global minimum at every iteration due to q-derivative. Further, the rate of convergence is proved as a superlinear in a local neighborhood of a minimum point based on q-derivative. Finally, the numerical experiments show better performance.