• 제목/요약/키워드: optimality function

검색결과 147건 처리시간 0.026초

OPTIMALITY AND DUALITY IN NONSMOOTH VECTOR OPTIMIZATION INVOLVING GENERALIZED INVEX FUNCTIONS

  • Kim, Moon-Hee
    • Journal of applied mathematics & informatics
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    • 제28권5_6호
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    • pp.1527-1534
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    • 2010
  • In this paper, we consider nonsmooth optimization problem of which objective and constraint functions are locally Lipschitz. We establish sufficient optimality conditions and duality results for nonsmooth vector optimization problem given under nearly strict invexity and near invexity-infineness assumptions.

단순선형회귀와 이차형식회귀모형을 중심으로 D-와 이분산 G-최적에 비교한 Iλ-최적실험기준의 특성연구 (Characteristics of Iλ-optimality Criterion compared to the D- and Heteroscedastic G-optimality with respect to Simple Linear and Quadratic Regression)

  • 김영일
    • 품질경영학회지
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    • 제21권2호
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    • pp.140-155
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    • 1993
  • The characteristics of $I_{\lambda}$-optimality, one of the linear criteria suggested by Fedorov (1972) are investigated with respect to the D-and heteroscedastic G-optimality in case of non-constant variance function. Though having limited results obtained from simple models, we may conclude that $I_{\lambda}$-optimality is sometimes preferred to the heteroscedastic G-optimality suggested newly bv Wong and Cook (1992) in the sense that the experimenter's belief in weighting function exists in $I_{\lambda}$-optimality criterion, not to mention its computational simplicity.

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ON FRACTIONAL PROGRAMMING CONTAINING SUPPORT FUNCTIONS

  • HUSAIN I.;JABEEN Z.
    • Journal of applied mathematics & informatics
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    • 제18권1_2호
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    • pp.361-376
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    • 2005
  • Optimality conditions are derived for a nonlinear fractional program in which a support function appears in the numerator and denominator of the objective function as well as in each constraint function. As an application of these optimality conditions, a dual to this program is formulated and various duality results are established under generalized convexity. Several known results are deduced as special cases.

$I{\lambda}$-최적실험계획의 특성에 대한 추가적인 연구

  • 김영일
    • Communications for Statistical Applications and Methods
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    • 제2권1호
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    • pp.55-63
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    • 1995
  • The characteristics of $I{\lambda}$-optimality are investigated with repsect to other experimental design's criteria, D-and G-optimality. The comparisons are based on D- and G-, and $I{\lambda}$-efficiencies using the Beta(p, q) distribution as a weighting function for $I{\lambda}$-optimality. Results indicate that serious consideration should be given to the $I{\lambda}$-optimality criterion especially when the error variance function is not homogeneous.

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NECESSARY AND SUFFICIENT OPTIMALITY CONDITIONS FOR FUZZY LINEAR PROGRAMMING

  • Farhadinia, Bahram
    • Journal of applied mathematics & informatics
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    • 제29권1_2호
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    • pp.337-349
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    • 2011
  • This paper is concerned with deriving necessary and sufficient optimality conditions for a fuzzy linear programming problem. Toward this end, an equivalence between fuzzy and crisp linear programming problems is established by means of a specific ranking function. Under this setting, a main theorem gives optimality conditions which do not seem to be in conflict with the so-called Karush-Kuhn-Tucker conditions for a crisp linear programming problem.

ON OPTIMALITY OF GENERALIZED OPTIMIZATION PROBLEMS ASSOCIATED WITH OPERATOR AND EXISTENCE OF (Tη; ξθ)-INVEX FUNCTIONS

  • Das, Prasanta Kumar
    • East Asian mathematical journal
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    • 제33권1호
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    • pp.83-102
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    • 2017
  • The main purpose of this paper is to introduce a pair new class of primal and dual problem associated with an operator. We prove the sufficient optimality theorem, weak duality theorem and strong duality theorem for these problems. The equivalence between the generalized optimization problems and the generalized variational inequality problems is studied in ordered topological vector space modeled in Hilbert spaces. We introduce the concept of partial differential associated (PDA)-operator, PDA-vector function and PDA-antisymmetric function to show the existence of a new class of function called, ($T_{\eta};{\xi}_{\theta}$)-invex functions. We discuss first and second kind of ($T_{\eta};{\xi}_{\theta}$)-invex functions and establish their existence theorems in ordered topological vector spaces.

OPTIMALITY AND DUALITY IN NONDIFFERENTIABLE MULTIOBJECTIVE FRACTIONAL PROGRAMMING USING α-UNIVEXITY

  • Gupta, Rekha;Srivastava, Manjari
    • Journal of applied mathematics & informatics
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    • 제32권3_4호
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    • pp.359-375
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    • 2014
  • In this paper, a multiobjective nondifferentiable fractional programming problem (MFP) is considered where the objective function contains a term involving the support function of a compact convex set. A vector valued (generalized) ${\alpha}$-univex function is defined to extend the concept of a real valued (generalized) ${\alpha}$-univex function. Using these functions, sufficient optimality criteria are obtained for a feasible solution of (MFP) to be an efficient or weakly efficient solution of (MFP). Duality results are obtained for a Mond-Weir type dual under (generalized) ${\alpha}$-univexity assumptions.

OPTIMALITY CONDITIONS AND DUALITY IN NONDIFFERENTIABLE ROBUST OPTIMIZATION PROBLEMS

  • Kim, Moon Hee
    • East Asian mathematical journal
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    • 제31권3호
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    • pp.371-377
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    • 2015
  • We consider a nondifferentiable robust optimization problem, which has a maximum function of continuously differentiable functions and support functions as its objective function, continuously differentiable functions as its constraint functions. We prove optimality conditions for the nondifferentiable robust optimization problem. We formulate a Wolfe type dual problem for the nondifferentiable robust optimization problem and prove duality theorems.

THE KARUSH-KUHN-TUCKER OPTIMALITY CONDITIONS IN INTERVAL-VALUED MULTIOBJECTIVE PROGRAMMING PROBLEMS

  • Hosseinzade, Elham;Hassanpour, Hassan
    • Journal of applied mathematics & informatics
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    • 제29권5_6호
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    • pp.1157-1165
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    • 2011
  • The Karush-Kuhn-Tucker (KKT) necessary optimality conditions for nonlinear differentiable programming problems are also sufficient under suitable convexity assumptions. The KKT conditions in multiobjective programming problems with interval-valued objective and constraint functions are derived in this paper. The main contribution of this paper is to obtain the Pareto optimal solutions by resorting to the sufficient optimality condition.