A recourse-based nonlinear programming (RBNP) method is developed for stream water quality management under uncertainty. It can not only reflect uncertainties expressed as interval values and probability distributions...
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A recourse-based nonlinear programming (RBNP) method is developed for stream water quality management under uncertainty. It can not only reflect uncertainties expressed as interval values and probability distributions but also address nonlinearity in the objective function. A 0-1 piecewise linearization approach and an interactive algorithm are advanced for solving the RBNP model. The RBNP is applied to a case of planning stream water quality management. The RBNP modeling system can provide an effective linkage between environmental regulations and economic implications expressed as penalties or opportunity losses caused by improper policies. The solutions can be used for generating a variety of alternatives under different combinations of pre-regulated targets, which are also associated with different water-quality-violation risk levels and varied potential economic penalty or loss values.
The nonlinear programming (NLP) is an optimization technique that minimizes arbitrary nonlinear cost functions. To apply the NLP to real-time applications, however, the estimation of the gradient of the cost function ...
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The nonlinear programming (NLP) is an optimization technique that minimizes arbitrary nonlinear cost functions. To apply the NLP to real-time applications, however, the estimation of the gradient of the cost function is remained as a challenge. The extremum-seeking control (ESC) optimizes the cost functions in real-time, but it involves the complicated design of filters for simultaneous estimation of the gradient. In this paper, a complementary method that optimizes an arbitrary multivariable cost function in real-time is proposed. Taking the advantages of both NLP and ESC, the variables are updated by the steepest descent method of NLP, while the gradient of the cost function is continuously estimated by the amplitude modulation as in ESC. Unlike the ESC, the proposed method does not require the design of complicated filters. The optimization performance is verified by simulations on time-varying and noisy cost functions, as well as automatic controller tuning applications.
We present a VLSI-array-processor architecture for the implementation of a nonlinear programming algorithm that solves discrete-time optimal control problems for nonlinear systems with control constraints. We incorpor...
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We present a VLSI-array-processor architecture for the implementation of a nonlinear programming algorithm that solves discrete-time optimal control problems for nonlinear systems with control constraints. We incorporate this hardware module with a two-phase parallel computing method and develop a VLSI-array-processor architecture to implement a receding horizon controller for constrained nonlinear systems. On the basis of current VLSI technologies, the estimated computing time to obtain the receding-horizon feedback-control solution meets the realtime processing-system needs. (C) 1997 Elsevier Science Ltd.
Most research in robust optimization has been focused so far on inequality-only, convex conic programming with simple linear models for the uncertain parameters. Many practical optimization problems, however, are nonl...
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Most research in robust optimization has been focused so far on inequality-only, convex conic programming with simple linear models for the uncertain parameters. Many practical optimization problems, however, are nonlinear and nonconvex. Even in linear programming, the coefficients may still be nonlinear functions of the uncertain parameters. In this paper, we propose robust formulations that extend the robust-optimization approach to a general nonlinear programming setting with parameter uncertainty involving both equality and inequality constraints. The proposed robust formulations are valid in a neighborhood of a given nominal parameter value and are robust to the first-order, thus suitable for applications where reasonable parameter estimations are available and uncertain variations are moderate.
In this paper, several interactive procedures for solving multiple criteria nonlinear programming problems have been developed. These are based on the generalized reduced gradient method for solving single objective n...
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In this paper, several interactive procedures for solving multiple criteria nonlinear programming problems have been developed. These are based on the generalized reduced gradient method for solving single objective nonlinear programming problems. They can handle maximization problems with nonlinear concave objectives, nonlinear convex constraints and an implicit quasi-concave preference function of the decision maker. The interactive procedures work with information of varying degrees of accuracy from the decision maker, thereby extending and strengthening a number of existing methods. [ABSTRACT FROM AUTHOR]
Leafy green vegetables are highly susceptible to microbial contamination because they are minimally processed. Pathogenic bacteria of concern include Escherichia coli O157:H7, Salmonella spp., and Listeria monocytogen...
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Leafy green vegetables are highly susceptible to microbial contamination because they are minimally processed. Pathogenic bacteria of concern include Escherichia coli O157:H7, Salmonella spp., and Listeria monocytogenes. Leafy greens are a highly perishable commodity, and in some cases have a postharvest shelf-life limited to one week. This study provides an approach to optimize storage temperature of leafy greens in the supply chain, considering the cost of refrigeration, sensory quality parameters (i.e., fresh appearance, wilting, browning, and off-odor), and microbial safety using nonlinear programming (NLP). The loss of sensory quality parameters was expressed as Arrhenius equations and pathogen growth were represented by three-phase linear (primary) and square-root (secondary) models. The objective function was refrigeration cost, which was to be minimized. The constraints were growth of pathogens and the loss of sensory characteristics. An interactive graphical user interface was developed in MATLAB. Pathogen growth is of more concern than loss of sensory quality in fresh-cut Iceberg lettuce when considering a shelf-life of up to two days, and the model indicates is difficult to maintain sensory qualities for longer shelf-life values. Browning is of maximum concern for fresh-cut Iceberg and Romaine lettuce, whereas off-odor is the biggest concern for fresh-cut chicory. (C) 2016 Elsevier Ltd. All rights reserved.
In this paper, a class of functions, named as r-semipreinvex functions, which is generalization of semipreinvex functions and r-preinvex functions, is introduced. Example is given to show that there exists function wh...
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In this paper, a class of functions, named as r-semipreinvex functions, which is generalization of semipreinvex functions and r-preinvex functions, is introduced. Example is given to show that there exists function which is r-semipreinvex function, but is not semipreinvex function. Furthermore, some basic characterizations of r-semipreinvex functions are established. At the same time, some optimality results are obtained in nonlinear programming problems.
In this paper, a new method is presented to deal with nonconvex nonlinear inequality constrained problem by using the idea of epsilon-effective set. It is only required to solve two systems of linear equations per sin...
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In this paper, a new method is presented to deal with nonconvex nonlinear inequality constrained problem by using the idea of epsilon-effective set. It is only required to solve two systems of linear equations per single iteration. The theoretical analysis shows that the algorithm is global convergence under some suitable conditions. (c) 2004 Elsevier Inc. All rights reserved.
The aim of this paper is to show that the theorem on the global convergence of the Newton interior-point (IP) method presented in Ref. 1 can be proved under weaker assumptions. Indeed, we assume the boundedness of the...
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The aim of this paper is to show that the theorem on the global convergence of the Newton interior-point (IP) method presented in Ref. 1 can be proved under weaker assumptions. Indeed, we assume the boundedness of the sequences of multipliers related to nontrivial constraints, instead of the hypothesis that the gradients of the inequality constraints corresponding to slack variables not bounded away from zero are linearly independent. By numerical examples, we show that, in the implementation of the Newton IP method, loss of boundedness in the iteration sequence of the multipliers detects when the algorithm does not converge from the chosen starting point.
This paper develops a novel nonlinear numerical method to perform shakedown analysis of structures subjected to variable loads by means of nonlinear programming techniques and the displacement-based finite element met...
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This paper develops a novel nonlinear numerical method to perform shakedown analysis of structures subjected to variable loads by means of nonlinear programming techniques and the displacement-based finite element method. The analysis is based on a general yield function which can take the form of most soil yield criteria (e.g. the Mohr-Coulomb or Drucker-Prager criterion). Using an associated flow rule, a general yield criterion can be directly introduced into the kinematic theorem of shakedown analysis without linearization. The plastic dissipation power can then be expressed in terms of the kinematically admissible velocity and a nonlinear formulation is obtained. By means of nonlinear mathematical programming techniques and the finite element method, a numerical model for kinematic shakedown analysis is developed as a nonlinear mathematical programming problem subject to only a small number of equality constraints. The objective function corresponds to the plastic dissipation power which is to be minimized and an upper bound to the shakedown load can be calculated. An effective, direct iterative algorithm is then proposed to solve the resulting nonlinear programming problem. The calculation is based on the kinematically admissible velocity with one-step calculation of the elastic stress field. Only a small number of equality constraints are introduced and the computational effort is very modest. The effectiveness and efficiency of the proposed numerical method have been validated by several numerical examples. (c) 2006 Elsevier Ltd. All rights reserved.
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