New concepts of generalized (rho, theta)-eta invex functions for non-differentiable functions and generalized (rho, theta)-eta invariant monotone operators for set-valued mappings are introduced. The relationships bet...
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New concepts of generalized (rho, theta)-eta invex functions for non-differentiable functions and generalized (rho, theta)-eta invariant monotone operators for set-valued mappings are introduced. The relationships between generalized (rho, theta)-eta invexity of functions and generalized (rho, theta)-eta invariant monotonicity of the corresponding Clarke's subdifferentials are studied. Some of our results are extension and improvement of some results obtained in (Jabarootion and Zafarani (2006);Behera et al. (2008). Copyright (C) 2009 C. Liu and X. Yang.
This paper deals with the project selection problem. Project selection problem is one of the problems arose firstly in the field of operations research following some production concepts from primary product mix probl...
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This paper deals with the project selection problem. Project selection problem is one of the problems arose firstly in the field of operations research following some production concepts from primary product mix problem. Afterward, introduction of managerial considerations into the project selection problem have emerged qualitative factors and criteria to be regarded as well as quantitative ones. To overcome both kinds of criteria, an analytic network process is developed in this paper enhanced with fuzzy sets theory to tackle the vagueness of experts' comments to evaluate the alternatives. Additionally, a modified version of Least-Square method through a non-linear programming model is augmented to the developed group decision making structure in order to elicit the final weights from comparison matrices. Finally, a case study is considered by which developed structure in this paper is validated. Moreover, a sensitivity analysis is performed to validate the response of the model with respect to the condition alteration.
In this study, line-up computational algorithm (LCA) is applied to estimate the parameters of nonlinear chemical systems under the framework of the integration approach. Four benchmark problems are provided in this pa...
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The Total Cost of Ownership (TCO) for developing communication services comprises from two parts;CAPital EXpenditure (CAPEX) and OPerational EXpenditure (OPEX). These two types of costs are interrelated and affect any...
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A novel upper bound limit method for rock slope stability analysis is developed in this *** element method (BEM) is employed to discrete the area concerned and to construct a kinematically admissible velocity field.A ...
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A novel upper bound limit method for rock slope stability analysis is developed in this *** element method (BEM) is employed to discrete the area concerned and to construct a kinematically admissible velocity field.A nonlinear programming model for the upper bound limit of safety factor of rock slopes is formulated,in which the velocity field satisfies the constrain conditions including the Mohr-Coulomb yield criterion on the slide surface,the associated flow rule, boundary conditions,as well as the virtual work of the block *** model is solved by the complex shape method.A wedge-block in a rock slope is studied,which verified the efficiency of the *** the end,the application to the intake slope of Xiaowan Project shows the practicability of the method to the slope.
In this paper, we investigate the problem of power optimization in CMOS circuits using gate sizing and voltage selection for a given clock period specification. Several solutions have been proposed for power optimizat...
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ISBN:
(纸本)076952365X
In this paper, we investigate the problem of power optimization in CMOS circuits using gate sizing and voltage selection for a given clock period specification. Several solutions have been proposed for power optimization during gate sizing and voltage selection. Since the problem formulation is nonlinear in nature, nonlinear programming (NLP) based solutions will yield better accuracy, however, convergence is difficult for large circuits. On the other hand, heuristic solutions will result in faster but less accurate solutions. In this work, we propose a new algorithm for gate sizing and voltage selection based on NLP for power optimization. The algorithm uses gate level heuristics for delay assignment which disassociates the delays of all the paths to the individual gate level, and each gate is then separately optimized for power with its delay constraint. Since the optimization is done at the individual gate level, NLP converges quickly while maintaining accuracy. Experimental results are presented for ISCAS benchmarks which clearly illustrate the efficacy of the proposed solution.
This paper develops a novel method for solving a type of nonlinear programming model with all fuzzy coefficients (AFCNP). For a decision maker specified credibility level, by presenting the equivalent deterministic fo...
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ISBN:
(纸本)3540283250
This paper develops a novel method for solving a type of nonlinear programming model with all fuzzy coefficients (AFCNP). For a decision maker specified credibility level, by presenting the equivalent deterministic forms of fuzzy inequality constraints and fuzzy objective, the fuzzy model is converted into a crisp constrained nonlinear programming model with parameter (CPNP). An improved genetic algorithm is presented to solve the CPNP and obtain the crisp optimal solution of AFCNP for specified credibility level.
This paper focuses on the improvement of the concentration and productivity of 1,3-propanediol from continuous fermentation of glycerol by Klebsiella pneumoniae.A nonlinear steady-state optimization model is presented...
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This paper focuses on the improvement of the concentration and productivity of 1,3-propanediol from continuous fermentation of glycerol by Klebsiella pneumoniae.A nonlinear steady-state optimization model is presented according to engineering background.A new linear approximating method has been developed in view of the feature of the optimization model. Computer simulation is used for this paper,and the numerical simulation is in accordance with experimental *** numerical results illustrate the validity and efficiency of the *** results presented in this work can be used as guidelines for choosing proper operating parameters to get higher concentration or productivity.
In this paper, a uniform method is presented for computing the minimum translational distance (MTD) between a pair of ellipsoids. This article deduces a necessary and sufficient condition of the witness point-pair whi...
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ISBN:
(纸本)9781424442843
In this paper, a uniform method is presented for computing the minimum translational distance (MTD) between a pair of ellipsoids. This article deduces a necessary and sufficient condition of the witness point-pair which achieve MTD value and reliable criteria for determining their spatial relation. Experimental results show the algorithm converge after a few iterations whether two objects overlap or not and perform better than other algorithms.
Gradient type methods are widely used approaches for nonlinear programming in image processing, due to their simplicity, low memory requirement and ability to provide medium-accurate solutions without excessive comput...
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ISBN:
(纸本)9781617388767
Gradient type methods are widely used approaches for nonlinear programming in image processing, due to their simplicity, low memory requirement and ability to provide medium-accurate solutions without excessive computational costs. In this work we discuss some improved gradient projection methods for constrained optimization problems in image deblurring and denoising. Crucial feature of these approaches is the combination of special steplength rules and scaled gradient directions, appropriately designed to achieve a better convergence rate. Convergence results are given by exploiting monotone or nonmonotone line-search strategies along the feasible direction. The effectiveness of the algorithms is evaluated on the problems arising from the maximum likelihood approach to the deconvolution of images and from the edge-preserving removal of Poisson noise. Numerical results obtained by facing large scale problems involving images of several mega-pixels on graphics processors are also reported.
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