Results 11 to 20 of about 1,264 (229)
Duality of (h,φ)-Multiobjective Programming Involving Generalized Invex Functions [PDF]
Journal of Applied Mathematics, 2012 In the setting of Ben-Tal's generalized algebraic operations, this paper deals with Mond-Weir type dual theorems of multiobjective programming problems involving generalized invex functions.
GuoLin Yu
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Invex functions and constrained local minima [PDF]
Bulletin of the Australian Mathematical Society, 1981 If a certain weakening of convexity holds for the objective and all constraint functions in a nonconvex constrained minimization problem, Hanson showed that the Kuhn-Tucker necessary conditions are sufficient for a minimum. This property is now generalized to a property, called K-invex, of a vector function in relation to a convex cone K.
B. D. Craven
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INFINITELY MANY INVEX FUNCTIONS WITHOUT CONVEXITY [PDF]
Bulletin of informatics and cyberneticsThe paper under review provides several examples of smooth and nonsmooth invex functions that are not necessarily convex. However, as the authors themselves mention, invexity has not yet found a significant application in mathematical optimization (or in any other field).
Shunsuke Shiraishi +2 more
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Further Study on Strong Lagrangian Duality Property for Invex Programs via Penalty Functions [PDF]
Journal of Inequalities and Applications, 2010 We apply the quadratic penalization technique to derive strong Lagrangian duality property for an inequality constrained invex program. Our results extend and improve the corresponding results in the literature.
Huang XX, Zhang J
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Invexity of supremum and infimum functions [PDF]
Bulletin of the Australian Mathematical Society, 2002 Under suitable assumptions we establish the formulas for calculating generalised gradients and generalised directional derivatives in the Clarke sense of the supremum and the infimum of an infinite family of Lipschitz functions. From these results we derive the results ensuring such a supremum or infimum are an invex function when all functions of the ...
Nguyen Xuan Ha, Do Van Luu
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Quantum ostrowski type inequalities for pre-invex functions
Mathematica Slovaca, 2022 Abstract In this paper, using the quantum derivatives and quantum integrals, we prove some new quantum Ostrowski’s type inequalities for pre-invex functions. Furthermore, in the special cases of newly developed inequalities, we obtain different new and existing Ostrowski’s type inequalities.
Ali, Muhammad Aamir +3 more
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Semi-invex functions and their subdifferentials [PDF]
Bulletin of the Australian Mathematical Society, 1997 We introduce the notion of semi-invex function (non-smooth) and the associated subdifferential. We study their properties and establish the conditions for optimality in constrained and unconstrained minimisation problems.
Dutta, J., Vetrivel, V., Nanda, S.
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Minimax fractional programming involving generalised invex functions [PDF]
The ANZIAM Journal, 2003 AbstractThe convexity assumptions for a minimax fractional programming problem of variational type are relaxed to those of a generalised invexity situation. Sufficient optimality conditions are established under some specific assumptions. Employing the existence of a solution for the minimax variational fractional problem, three dual models, the Wolfe ...
Lai, H. C., Liu, J. C.
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Generalized Differentiable -Invex Functions and Their Applications in Optimization [PDF]
Advances in Operations Research, 2012 The concept of -convex function and its generalizations is studied with differentiability assumption. Generalized differentiable -convexity and generalized differentiable -invexity are used to derive the existence of optimal solution of a general optimization problem.
Sangeeta Jaiswal, Geetanjali Panda
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Optimality and Duality of Semi-Preinvariant Convex Multi-Objective Programming Involving Generalized (F,α,ρ,d)-I-Type Invex Functions [PDF]
MathematicsMultiobjective programming refers to a mathematical problem that requires the simultaneous optimization of multiple independent yet interrelated objective functions when solving a problem.
Rongbo Wang, Qiang Feng
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