The problems of feedback minimax control for parabolic variational inequalities are considered. algorithms solving these problems which are stable with respect to informational noises and computational errors are outl...
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The problems of feedback minimax control for parabolic variational inequalities are considered. algorithms solving these problems which are stable with respect to informational noises and computational errors are outlined. The algorithms are based on the principle of feedback control with a model [1]. (C) 2000 Academie des sciences/Editions scientifiques et medicales Elsevier SAS.
Queueing network models with finite capacity queues and blocking are used to represent systems with resource constraints, such as production, communication and computer systems. Various blocking mechanisms have been d...
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Queueing network models with finite capacity queues and blocking are used to represent systems with resource constraints, such as production, communication and computer systems. Various blocking mechanisms have been defined in the literature to represent the different behaviours of real systems with limited resources. Queueing networks with blocking have a product form solution under special constraints, for different blocking mechanisms. In this paper we present a Mean Value Analysis for the computation of performance measures in product form solution queueing networks with repetitive service blocking. Basic to the derivation of this algorithm are recursive expressions for the performance indices that are a non trivial generalisation of those derived for the Mean Value Analysis of product form queueing networks without blocking. In this paper we give a formal derivation of several recursive relations as well as details on their implementation. A few basic examples are evaluated with the techniques discussed in this paper to show the advantages of this approach. (C) 1999 Elsevier Science B.V. All rights reserved.
Recently the author introduced a package of algorithms, called MANPAK, for effective computations on implicitly defined submanifolds of R(n). Here algebraically explicit differential algebraic equations (DAEs) are con...
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Recently the author introduced a package of algorithms, called MANPAK, for effective computations on implicitly defined submanifolds of R(n). Here algebraically explicit differential algebraic equations (DAEs) are considered;that is, DAEs in which either the algebraic equations and/or the algebraic variables are explicitly specified. Existence proofs for several types of such DAEs of index one, two, and three are given, which directly suggest computational approaches. This is used in the development of solution algorithms for these DAEs, all of them intrinsically based on the MANPAK routines. Some numerical examples for the methods are included.
In this paper we present a Mean Value Analysis (MVA) algorithm for the computation of performance measures in Product Form Solution Stochastic Petri Nets. Basic to the derivation of this algorithm are recursive expres...
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In this paper we present a Mean Value Analysis (MVA) algorithm for the computation of performance measures in Product Form Solution Stochastic Petri Nets. Basic to the derivation of this algorithm are recursive expressions for the performance indices that are a non-trivial generalization of those derived for the MVA of multiple class product form queueing networks. In this paper we give a formal derivation of several recursive relations as well as details on their implementation. The advantage that MVA provides for the development of approximation techniques is also investigated and a first method that gives satisfactory results is presented. A few basic examples are evaluated with the techniques discussed in this paper to show the advantages of this approach.
In this paper, we study the production scheduling problem in a competitive environment. Two firms produce the same product and compete in a market. The demand is random and so is the production capacity of each firm, ...
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In this paper, we study the production scheduling problem in a competitive environment. Two firms produce the same product and compete in a market. The demand is random and so is the production capacity of each firm, due to random breakdowns. We consider a finite planning horizon. The scheduling problem is formulated as a finite dynamic game. algorithms are developed to determine the security, hazard, and Nash policies. Numerical examples are discussed. A single-firm optimization model is also analyzed and it is observed that the production control policy from the single-firm optimization model may not perform well in a competitive environment.
Mathematical models often involve differentiable manifolds that are implicitly defined as the solution sets of systems of nonlinear equations. The resulting computational tasks differ considerably from those arising f...
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Mathematical models often involve differentiable manifolds that are implicitly defined as the solution sets of systems of nonlinear equations. The resulting computational tasks differ considerably from those arising for manifolds defined in parametric form. Here a collection of algorithms is presented for performing a range of essential tasks on general, implicitly specified submanifolds of a finite dimensional space. This includes algorithms for determining local parametrizations and their derivatives, and for evaluating quantities related to the curvature with sensitivity measures. The methods have been implemented as a FORTRAN 77 package, called MANPAK.
An iterative technique for the computation of approximate performance indices of a class of stochastic Petri nets models is presented. The proposed technique is derived from the mean value analysis algorithm for produ...
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An iterative technique for the computation of approximate performance indices of a class of stochastic Petri nets models is presented. The proposed technique is derived from the mean value analysis algorithm for product form solution stochastic Petri nets. in this paper, we apply the approximation technique to stochastic marked graphs;In principle, the proposed technique can be used for other stochastic Petri net subclasses in the paper, some of these possible applications are presented. Several examples are presented in order to validate the approximate results.
A parallelization of an algorithm of solution of the manipulator inverse dynamics problem is presented. The algorithm is based on the Lagrange formalism and makes use of (3x3) rotation matrices. A version of the algor...
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A parallelization of an algorithm of solution of the manipulator inverse dynamics problem is presented. The algorithm is based on the Lagrange formalism and makes use of (3x3) rotation matrices. A version of the algorithm with prediction of temporary data is also described. The computational complexity of the parallel algorithm with respect to the number of degrees of freedom of the manipulator and to the number of processors used is considered.
Most algorithms for estimating high breakdown regression estimators in linear regression rely on finding the least squares fit to manyp-point elemental sets, wherepis the dimension of the X matrix. Such an approach is...
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Most algorithms for estimating high breakdown regression estimators in linear regression rely on finding the least squares fit to manyp-point elemental sets, wherepis the dimension of the X matrix. Such an approach is computationally infeasible in nonlinear regression. This article presents a new algorithm for computing high breakdown estimates in nonlinear regression that requires only a small number of least squares fits toppoints. The algorithm is used to compute Rousseeuw's least median of squares (LMS) estimate and Yohai's MM estimate in both simulations and examples. It is also used to compute bootstrapped and Monte Carlo Standard error estimates for MM estimates, which are compared with asymptotic Standard errors (ASE's). Using the PROGRESS algorithm for a two-parameter nonlinear model with sample size 30 would require finding the least squares fit to 435 two-point subsets of the data. In the settings considered in this article, the proposed algorithm performs just as well with 25 as with 435 least squares fits, thus substantially reducing computation time. Using the new algorithm to compare Standard error estimates for MM estimates reveals that. at least in the setting considered here, bootstrapped and to a lesser extent ASE's become increasingly unreliable as the percentage of outliers increases. In one example presented, the high breakdown estimates are useful in determining that a point appearing to be an outlier in the least squares analysis probably should not be considered an outlier. In the other example, the least squares analysis reveals no outliers and suggests that the model is inappropriate for the data. The residual plots using high breakdown estimates reveal that two points are outliers, and the model provides a reasonable fit to the remainder of the data.
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