The Experts below are selected from a list of 309 Experts worldwide ranked by ideXlab platform
Z. Jabeen - One of the best experts on this subject based on the ideXlab platform.
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On fractional programming containing support Functions
Journal of Applied Mathematics and Computing, 2005Co-Authors: I. Husain, Z. JabeenAbstract: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.
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On nonlinear programming with support Functions
Journal of Applied Mathematics and Computing, 2002Co-Authors: I. Husain, Z. JabeenAbstract:Optimality conditions are derived for a nonliear program in which a support Function appears in the objective as well as in each Constraint Function. Wolfe and Mond-Weir type duals to this program are presented and various dualityresults are established under suitable convexity and generalized convexity assumptions. Special cases that often occur in the literature are those in which a support Function is the square root of a positive semidefinite quadratic form or an Lp norm. It is pointed out that these special cases can easily be generated from our results.
I. Husain - One of the best experts on this subject based on the ideXlab platform.
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On a Control Problem Containing Support Functions
American Journal of Operations Research, 2014Co-Authors: I. Husain, A. Ahmed, Abdul Raoof ShahAbstract:A control problem containing support Functions in the integrand of the objective of the Functional as well as in the inequality Constraint Function is considered. For this problem, Fritz John and Karush-Kuhn-Tucker type necessary optimality conditions are derived. Using Karush-Kuhn-Tucker type optimality conditions, Wolfe type dual is formulated and usual duality theorems are established under generalized convexity conditions. Special cases are generated. It is also shown that our duality results have linkage with those of nonlinear programming problems involving support Functions.
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On fractional programming containing support Functions
Journal of Applied Mathematics and Computing, 2005Co-Authors: I. Husain, Z. JabeenAbstract: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.
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On nonlinear programming with support Functions
Journal of Applied Mathematics and Computing, 2002Co-Authors: I. Husain, Z. JabeenAbstract:Optimality conditions are derived for a nonliear program in which a support Function appears in the objective as well as in each Constraint Function. Wolfe and Mond-Weir type duals to this program are presented and various dualityresults are established under suitable convexity and generalized convexity assumptions. Special cases that often occur in the literature are those in which a support Function is the square root of a positive semidefinite quadratic form or an Lp norm. It is pointed out that these special cases can easily be generated from our results.
Saifullah Muhammad - One of the best experts on this subject based on the ideXlab platform.
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Bayesian analysis of jujube canopy transpiration models: Does embedding the key environmental factor in Jarvis canopy resistance sub-model always associate with improving transpiration modeling?
Agricultural Water Management, 2020Co-Authors: Dianyu Chen, Kuolin Hsu, Xingwu Duan, Youke Wang, Xinguang Wei, Saifullah MuhammadAbstract:Abstract The Jarvis canopy resistance sub-model is commonly used in transpiration modelling, although its optimal structure is rarely studied. It is still not fully clear that to what extent transpiration modeling may differ if using different Constraint Function forms for key environmental variable in Jarvis sub-model. In this study, various Jarvis canopy resistance sub-model configurations were embedded in the Penman-Monteith model to compare their ability to model daily transpiration of rain-fed jujube (Ziziphus jujuba Mill.) plantations where soil moisture is a key factor of tree water use. Parameters were calibrated using the Bayesian Markov Chain Monte Carlo (MCMC) simulation technique and model comparison was quantified using Deviance Information Criterion (DIC). The results showed significant differences in model performance between the Constraint Function forms of soil water content. The difference in DIC between the model with the best Constraint Function form and the other two forms reached 37.66–50.94, much higher than the evaluation criteria for significance (larger than 7). When the best Constraint Function form was used, the performance of the transpiration model improved. The model performance worsened when the other Constraint Function forms were used, even worse than those without consideration for soil water content. However, only slight differences in model performance were detected for the Constraint Function forms of temperature, vapor pressure deficit and photosynthetically active radiation. Using the best configuration of Jarvis canopy resistance sub-model, daily transpiration of jujube plantation was well estimated with overall good accuracy and acceptable uncertainty. The predictions and observations were highly correlated (R2 = 0.87 for calibration and R2 = 0.80 for validation). The results suggested that different Constraint Function forms of an environmental factor contributed differently to transpiration model performance, and the situation was different for different environmental factors. Including the key environmental factor in the Jarvis canopy resistance sub-model will not always improve the performance of transpiration models.
Sandro Wartzack - One of the best experts on this subject based on the ideXlab platform.
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Sensitivity Analysis of features in tolerancing based on Constraint Function level sets
Reliability Engineering & System Safety, 2015Co-Authors: Philipp Ziegler, Sandro WartzackAbstract:Abstract Usually, the geometry of the manufactured product inherently varies from the nominal geometry. This may negatively affect the product Functions and properties (such as quality and reliability), as well as the assemblability of the single components. In order to avoid this, the geometric variation of these component surfaces and associated geometry elements (like hole axes) are restricted by tolerances. Since tighter tolerances lead to significant higher manufacturing costs, tolerances should be specified carefully. Therefore, the impact of deviating component surfaces on Functions, properties and assemblability of the product has to be analyzed. As physical experiments are expensive, methods of statistical tolerance analysis tools are widely used in engineering design. Current tolerance simulation tools lack of an appropriate indicator for the impact of deviating component surfaces. In the adoption of Sensitivity Analysis methods, there are several challenges, which arise from the specific framework in tolerancing. This paper presents an approach to adopt Sensitivity Analysis methods on current tolerance simulations with an interface module, which bases on level sets of Constraint Functions for parameters of the simulation model. The paper is an extension and generalization of Ziegler and Wartzack [1] . Mathematical properties of the Constraint Functions (convexity, homogeneity), which are important for the computational costs of the Sensitivity Analysis, are shown. The practical use of the method is illustrated in a case study of a plain bearing.
Pavel A. Bouzinov - One of the best experts on this subject based on the ideXlab platform.
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a finite element procedure for the analysis of thermo mechanical solids in contact
Computers & Structures, 2000Co-Authors: Daniel Pantuso, Klaus-jürgen Bathe, Pavel A. BouzinovAbstract:Abstract We present a finite element procedure for the analysis of fully coupled thermo-elasto-plastic response of solids including contact conditions. The continuum mechanics formulation for the solid and contact conditions is summarized and effective finite element techniques for solution are given. The Constraint Function method is employed to impose the contact conditions at the Gauss points of the contact surface. Other procedures widely used in finite element analysis can be considered as particular cases of the Constraint Function method discussed herein.
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On the Constraint Function method for contact problems
Computers & Structures, 1997Co-Authors: Klaus-jürgen Bathe, Pavel A. BouzinovAbstract:Abstract The objective in this paper is to present some theoretical insight and valuable numerical experiences for the analysis of contact problems. We review the theoretical basis of the Constraint Function method for general contact problems and discuss some important characteristics of the method. In the presentation, we consider static and dynamic conditions. We then give numerical experiences with the method through the solution of some demonstrative test problems and through the results obtained in some industrial analysis cases.