Results 141 to 150 of about 565 (171)

On Characterizations of Prequasi-Invex Functions

Journal of Optimization Theory and Applications, 2004
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Luo, H. Z., Xu, Z. K.
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Multiobjective programming with new invexities

Optimization Letters, 2012
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Maria Viorica Stefanescu, Massimiliano Ferrara, Anton Stefanescu   +2 more
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Invexity in multifunction optimization

Numerical Functional Analysis and Optimization, 1991
The concept of invex function is extended to arbitrary multifunctions, without requiring any differentiability property. Relations with the usual invexity for functions are established. For minimization of a vector multifunction objective, subject to a multiftmction inclusion constraint, necessary Lagrangian conditions are obtained, which become ...
P.H. Sach, B.D. Craven
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Semi-invexity and pre-invexity

2010
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Nanda, S, Pini, R
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Fractional Programming with Invexity

1999
Consider the nonlinear fractional programming problem: $$\mathop{{\min }}\limits_{{x \in {{X}_{0}}}} f\left( x \right)/g\left( x \right) subject to h\left( x \right) \leqslant 0, $$ (4.1) . Recently, Khan and Hanson gave sufficient conditions for optimality, and established duality results, assuming that f and -g are invex with respect to a ...
B. D. Craven, B. Mond
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Generalized Nonsmooth Invexity

Journal of Information and Optimization Sciences, 1994
Abstract In this paper sufficient optimality conditions and duality results are established for a nonlinear programming problem without differentiability assumption on the data wherein Clarke’s generalized gradient is used to define invexity, pβeudoinvexity and quasiinvexity for Lipβchitz functions.
R. N. Kaul, S. K. Suneja, C. S. Lalitha
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Multiobjective programming under d-invexity

European Journal of Operational Research, 2002
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(p,r)-Invexity in multiobjective programming

European Journal of Operational Research, 2004
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Optimization with generalized invexity

Optimization, 2005
Constrained optimization is studied, with nonsmooth (Lipschitz) functions in abstract spaces and cone-constraints. Some more general Lagrangian necessary conditions are obtained, using strict minimum and approximation methods. These conditions are sufficient for a minimum under generalized invex assumptions.
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-invex-infine functions and applications

Nonlinear Analysis: Theory, Methods & Applications, 2012
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