Zobrazeno 1 - 10
of 198
pro vyhledávání: '"Shashi Kant Mishra"'
Publikováno v:
Results in Control and Optimization, Vol 17, Iss , Pp 100486- (2024)
In this article, we study nonconvex multiobjective fractional programming problems involving E-differentiable functions (MFPE). We establish the E-Karush–Kuhn–Tucker (E-KKT) sufficient E-optimality conditions for nonsmooth vector optimization pro
Externí odkaz:
https://doaj.org/article/93e890e6381a4488ac5c3266feb3172a
Publikováno v:
Journal of Inequalities and Applications, Vol 2023, Iss 1, Pp 1-19 (2023)
Abstract Integral inequalities with generalized convexity play an important role in both applied and theoretical mathematics. The theory of integral inequalities is currently one of the most rapidly developing areas of mathematics due to its wide ran
Externí odkaz:
https://doaj.org/article/3a6cca4e6c6a4fe38714ca1c8f4c2a83
Publikováno v:
Mathematics, Vol 11, Iss 23, p 4857 (2023)
Quantum computing is an emerging field that has had a significant impact on optimization. Among the diverse quantum algorithms, quantum gradient descent has become a prominent technique for solving unconstrained optimization (UO) problems. In this pa
Externí odkaz:
https://doaj.org/article/e9133b094fdb4e228845d2b825070ac3
Publikováno v:
Journal of Inequalities and Applications, Vol 2021, Iss 1, Pp 1-15 (2021)
Abstract In this paper, we introduce ( h 1 , h 2 ) $(h_{1},h_{2})$ -preinvex interval-valued function and establish the Hermite–Hadamard inequality for preinvex interval-valued functions by using interval-valued Riemann–Liouville fractional integ
Externí odkaz:
https://doaj.org/article/ad986f1307ef4f8aadaab401f22c12db
Autor:
Mohammad Esmael Samei, Ahmad Ahmadi, Sayyedeh Narges Hajiseyedazizi, Shashi Kant Mishra, Bhagwat Ram
Publikováno v:
Journal of Inequalities and Applications, Vol 2021, Iss 1, Pp 1-33 (2021)
Abstract This paper deals with the existence of nonnegative solutions for a class of boundary value problems of fractional q-differential equation D q σ c [ k ] ( t ) = w ( t , k ( t ) , c D q ζ [ k ] ( t ) ) ${}^{c}\mathcal{D}_{q}^{\sigma }[k](t)
Externí odkaz:
https://doaj.org/article/03b3d6df17af4a08a8037d75477408f3
Publikováno v:
Mathematics, Vol 11, Iss 6, p 1420 (2023)
This paper presents a modification of the q-BFGS method for nonlinear unconstrained optimization problems. For this modification, we use a simple symmetric positive definite matrix and propose a new q-quasi-Newton equation, which is close to the ordi
Externí odkaz:
https://doaj.org/article/53a3926478ed477aa3b6abf4e41f2145
Publikováno v:
Journal of Inequalities and Applications, Vol 2021, Iss 1, Pp 1-18 (2021)
Abstract In this paper, we consider the semidifferentiable case of an interval-valued minimization problem and establish sufficient optimality conditions and Wolfe type as well as Mond–Weir type duality theorems under semilocal E-preinvex functions
Externí odkaz:
https://doaj.org/article/042d85e3fff549e6bd5afd820505080a
Publikováno v:
Journal of Inequalities and Applications, Vol 2021, Iss 1, Pp 1-29 (2021)
Abstract A Polak–Ribière–Polyak (PRP) algorithm is one of the oldest and popular conjugate gradient algorithms for solving nonlinear unconstrained optimization problems. In this paper, we present a q-variant of the PRP (q-PRP) method for which b
Externí odkaz:
https://doaj.org/article/ca6feef7cdd34be59fb0ade57450784d
Autor:
Shashi Kant Mishra, Geetanjali Panda, Suvra Kanti Chakraborty, Mohammad Esmael Samei, Bhagwat Ram
Publikováno v:
Advances in Difference Equations, Vol 2020, Iss 1, Pp 1-24 (2020)
Abstract Variants of the Newton method are very popular for solving unconstrained optimization problems. The study on global convergence of the BFGS method has also made good progress. The q-gradient reduces to its classical version when q approaches
Externí odkaz:
https://doaj.org/article/8eaeb842f3fc4557a8fa1f4c2bd4310e
Autor:
Kin Keung Lai, Shashi Kant Mishra, Geetanjali Panda, Md Abu Talhamainuddin Ansary, Bhagwat Ram
Publikováno v:
AIMS Mathematics, Vol 5, Iss 6, Pp 5521-5540 (2020)
The q-gradient is the generalization of the gradient based on the q-derivative. The q-version of the steepest descent method for unconstrained multiobjective optimization problems is constructed and recovered to the classical one as q equals 1. In th
Externí odkaz:
https://doaj.org/article/1f1eb6096b334575855c5d9a89a31357