In this paper a non-linear programming model is developed for a typical factory which presents the optimal values and times for the electrical energy consumption based on doing activities and operations in factory. Mo...
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In this paper a non-linear programming model is developed for a typical factory which presents the optimal values and times for the electrical energy consumption based on doing activities and operations in factory. Model's appropriate parameters are been with due attention to define tariffs and limitations by distributions of electrical energy. Furthermore, the operational constraints of the typical factory are formulated and these constraints are merged with the constraints of appropriate consumption. (C) 2006 Elsevier Inc. All rights reserved.
In this paper, generalized gradient projection method is modified to solve non-linear programming with nonlinear equality constraints and in-equality constraints. The global convergence properties of the new method ar...
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In this paper, generalized gradient projection method is modified to solve non-linear programming with nonlinear equality constraints and in-equality constraints. The global convergence properties of the new method are discussed. Combining quasi-Newton method with our new method, quasi-Newton method is modified to solve non-linear programming with non-linear equality constraints and in-equality constraints. The numerical results illustrate that the new methods are effective.
This paper details the combined application of generalized linear models and non-linear mathematical programming to the reduction of defects in a complex manufacturing process. Poisson regression techniques were appli...
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This paper details the combined application of generalized linear models and non-linear mathematical programming to the reduction of defects in a complex manufacturing process. Poisson regression techniques were applied to the characterization of multiple-defect classes identified through visual inspection. A constrained gradient search algorithm was then utilized to locate optimal process operating parameters. An application of the combined approach resulted in significant improvements in the quality of manufactured printed circuit boards.
In this article, a constraint shifting homotopy method (CSHM) is proposed for solving non-linear programming with both equality and inequality constraints. A new homotopy is constructed, and existence and global conve...
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In this article, a constraint shifting homotopy method (CSHM) is proposed for solving non-linear programming with both equality and inequality constraints. A new homotopy is constructed, and existence and global convergence of a homotopy path determined by it are proven. All problems that can be solved by the combined homotopy interior point method (CHIPM) can also be solved by the proposed method. In contrast to the combined homotopy infeasible interior point method (CHIIPM), it needs a weaker regularity condition. And the starting point in the proposed method is not necessarily a feasible point or an interior point, so it is more convenient to be implemented than CHIPM and CHIIPM. Numerical results show that the proposed algorithm is feasible and effective.
An interactive algorithm to solve multiple-objective non-linear programming (MONLP) problems is proposed. In each iteration of the proposed algorithm, the decision-maker is presented with a solution and a set of direc...
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An interactive algorithm to solve multiple-objective non-linear programming (MONLP) problems is proposed. In each iteration of the proposed algorithm, the decision-maker is presented with a solution and a set of direction (trade-off) vectors indicating possible trade-offs. Using the decision-maker's preferred trade-off vector, a new current solution and the corresponding trade-off vectors are found. The proposed algorithm is illustrated with a numerical example of a replacement model. Finally, the method is compared with four other interactive multiple-objective algorithms.
This paper deals with the control of the von Mises stress at a boundary with homogeneous Neumann conditions. In order to solve this non-linear optimization problem in which the shape of the structural component must b...
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This paper deals with the control of the von Mises stress at a boundary with homogeneous Neumann conditions. In order to solve this non-linear optimization problem in which the shape of the structural component must be treated as design variable, the variation of the objective and constraint functions with the change in shape is to be determined. Performing an accurate design sensitivity analysis is a difficult task because the shape does not appear explicitly in the formulation and because of the error associated with the approximation of the domain during discretization. The sensitivity analysis is done here using methods of theory of notches. The results will be applied to a FE-model of the structural component. The iterative method for changing the design based on this direction of search works efficiently even for a large number of design variables as shown in Schnack (1977a, 1978a, 1978b, 1979, 1980, 1982, 1983, 1985). Truncation and/or cancellation errors associated with numerical gradient computation are avoided. Using a dynamic programming formulation (Schnack and Spörl, 1986) the existence of a solution for this problem will be discussed. An example with this procedure is presented for a shaft in bending.
In Gonzaga et al. [A globally convergent filter method for nonlinearprogramming, SIAM J. Optimiz. 14 (2003), pp. 646-669] we discuss general conditions to ensure global convergence of inexact restoration filter algor...
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In Gonzaga et al. [A globally convergent filter method for nonlinearprogramming, SIAM J. Optimiz. 14 (2003), pp. 646-669] we discuss general conditions to ensure global convergence of inexact restoration filter algorithms for non-linear programming. In this article we show how to avoid the Maratos effect by means of a second-order correction. The algorithms are based on feasibility and optimality phases, which can be either independent or not. The optimality phase differs from the original one only when a full Newton step for the tangential minimization of the Lagrangian is efficient but not acceptable by the filter method. In this case a second-order corrector step tries to produce an acceptable point keeping the efficiency of the rejected step. The resulting point is tested by trust region criteria. Under the usual hypotheses, the algorithm inherits the quadratic convergence properties of the feasibility and optimality phases. This article includes a comparison between classical Sequential Quadratic programming (SQP) and Inexact Restoration (IR) iterations, showing that both methods share the same asymptotic convergence properties.
In order to effectively avoid risks that might result in loss of failure in software development process, based on the experiences of software development and project management, this paper identifies 4 potential risk...
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ISBN:
(纸本)9781424421077
In order to effectively avoid risks that might result in loss of failure in software development process, based on the experiences of software development and project management, this paper identifies 4 potential risk factors specific to software development projects which are integrated with 6 stages in software development process, and proposes a non-linear programming model to optimize funds allocation to reduce the risks. The paper provides an example to validate the effectiveness of the model.
In this paper, we focus on solving non-linear programming (NLP) problems using quantum-behaved particle swarm optimization (QPSO). After a brief introduction to the original particle swarm optimization ( PSO), we desc...
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In this paper, we focus on solving non-linear programming (NLP) problems using quantum-behaved particle swarm optimization (QPSO). After a brief introduction to the original particle swarm optimization ( PSO), we describe the origin and development of QPSO, and the penalty function method for constrained NLP problems. The performance of QPSO is tested on some unconstrained and constrained benchmark functions and compared with PSO with inertia weight (PSO-In) and PSO with constriction factor (PSO-Co). The experimental results show that QPSO outperforms the traditional PSOs and is a promising optimization algorithm.
Filter approach is initially proposed by Fletcher and Leyffer in 2002. Because of promising numerical results, filter methods are recently attached importance to. If the objective function value or the constraint viol...
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Filter approach is initially proposed by Fletcher and Leyffer in 2002. Because of promising numerical results, filter methods are recently attached importance to. If the objective function value or the constraint violation is reduced, this step is accepted by a filter, which is the basic idea of the filter. In this paper, the filter technique is employed in a trust region algorithm. In every trial step, the step length is controlled by a trust region radius. Moreover, our purpose is not to reduce the objective function and constraint violation directly. To overcome some bad cases, we aim to reduce the degree of constraint violation and the entry of some function, and the function is a combination of the objective function and the degree of constraint violation. The algorithm in this paper requires neither Lagrangian multipliers nor strong decrease condition. In certain conditions, this method produces K-T points for the original problem. Moreover, Maratos effect can be avoided for our algorithm. (c) 2005 Elsevier Inc. All rights reserved.
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