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Articles 211 - 215 of 215

Full-Text Articles in Numerical Analysis and Computation

Capacitated Network Revenue Management Through Shadow Pricing, Mustapha Bouhtou, Madiagne Diallo, Laura Wynter Sep 2003

Capacitated Network Revenue Management Through Shadow Pricing, Mustapha Bouhtou, Madiagne Diallo, Laura Wynter

Research Collection School Of Computing and Information Systems

In this paper, we analyze a method that links Lagrange multipliers from a resource allocation problem to the problem of revenue or profit maximization. This technique, first proposed in the transportation science literature by [7] has important implications for telecommunication network pricing. Indeed, the framework provides a generalization of telecommunication resource allocation/shadow price-based schemes such as those of [6] and [9], in that it permits the optimization of the shadow prices themselves, through a computationally simple procedure. We analyze the extent to which revenue can be maximized on a network that uses shadow-price-based prices, and how to deal with cases …

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Application Of Vibrational Techniques In Determination Of Dynamic Properties Of Agricultural Products-State Of The Arton Of Vibrational Techniques In Determination Of Dynamic Properties Of Agricultural Products-State Of The Art, Silas Kajuna Dec 1999

Application Of Vibrational Techniques In Determination Of Dynamic Properties Of Agricultural Products-State Of The Arton Of Vibrational Techniques In Determination Of Dynamic Properties Of Agricultural Products-State Of The Art, Silas Kajuna

Tanzania Journal of Engineering and Technology (TJET)

Vibration is one of the techniques employed in the determination of dynamic properties of fruits and vegetables. It entails generation of a mechanical or acoustic vibrational signal which is propagated through the flesh of the agricultural material. A transducer is either attached or held close to the specimen to monitor the propagation of the signal through the specimen. The manner in which the signal is transmitted through the material is analyzed, and the dynamic properties of the specimen which relate to its firmness or its internal being are derived. The technique has been around for the past 30 years or …

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Multirate Time-Frequency Distributions, John R. O'Hair May 1994

Multirate Time-Frequency Distributions, John R. O'Hair

Theses and Dissertations

Multirate systems, which find application in the design and analysis of filter banks, are demonstrated to also be useful as a computational paradigm. It is shown that any problem which can be expressed a set of vector-vector, matrix-vector or matrix-matrix operations can be recast using multirate. This means all of numerical linear algebra can be recast using multirate as the underlying computational paradigm. As a non-trivial example, the multirate computational paradigm is applied to the problem of Generalized Discrete Time- Frequency Distributions GDTFD to create a new family of fast algorithms. The first of this new class of distributions is …

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An Interval Newton Method, E R. Hansen, R I. Greenberg May 1983

An Interval Newton Method, E R. Hansen, R I. Greenberg

Computer Science: Faculty Publications and Other Works

We introduce an interval Newton method for bounding solutions of systems of nonlinear equations. It entails three subalgorithms. The first is a Gauss-Seidel-type step. The second is a real (noninterval) Newton iteration. The third solves the linearized equations by elimination. We explain why each subalgorithm is desirable and how they fit together to provide solutions in as little as one-third or one-quarter the time required by Krawczyk's method [7] in our implementations.

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An Interval Arithmetic Newton Method For Solving Systems Of Nonlinear Equations, Ronald I. Greenberg, Eldon R. Hansen Apr 1982

An Interval Arithmetic Newton Method For Solving Systems Of Nonlinear Equations, Ronald I. Greenberg, Eldon R. Hansen

Computer Science: Faculty Publications and Other Works

We introduce an interval Newton method for bounding solutions of systems of nonlinear equations. It entails three sub-algorithms. The first is a Gauss-Seidel type step. The second is a real (non-interval) Newton iteration. The third solves the linearized equations by elimination. We explain why each sub-algorithm is desirable and how they fit together to provide solutions in as little as 1/3 to 1/4 the time required by a commonly used method due to Krawczyk.

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