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Gradient Estimation for a Class of Systems with Bulk Services: A Problem in Public Transportation

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Author Info
Felisa J. Vazquez-Abad () (Université de Montreal)
Bernd Heidergott () (Faculty of Economics and Business Administration, Vrije Universiteit Amsterdam)

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Abstract

This paper deals with a system where batch arrivals wait in a station until a server (a train) is available, at which moment it services all customers in waiting. This is an example of a bulk server, which has many applications in public transportation, telecommunications, computer resource allocation, and multiple access telecommuncation networks, among others. We consider a subway model and focus on a metro line serving a particular metro station. Denote the planned inter-departure time of this line by theta. The metro station is served by several other lines and passengers change trains at the station. Traveling times of trains are assumed to be given by fixed times and an additional stochastic noise. We perform a sensitivity analysis of the total delay of passengers waiting for the "<&theta>" line with respect to theta. We establish a smoothed perturbation analysis (SPA), a measure--valued differentiation (MVD), and a score function (SF) estimator. Numerical experiments are performed to compare the ensuing estimators. It turns out that the SPA and MVD estimators are intrinsically different and the model presented in this paper may serve as a counter--example to the widespread belief that SPA and MVD yield similar estimators.

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Publisher Info
Paper provided by Tinbergen Institute in its series Tinbergen Institute Discussion Papers with number 03-057/4.

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Date of creation: 07 Jul 2003
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Handle: RePEc:dgr:uvatin:20030057

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Related research
Keywords: sensitivity analysis; smoothed perturbation analysis; score function; measure-valued differentiation; bulk servers.;

Find related papers by JEL classification:
C15 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods: General - - - Statistical Simulation Methods
C61 - Mathematical and Quantitative Methods - - Mathematical Methods and Programming - - - Optimization Techniques; Programming Models; Dynamic Analysis
C44 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods: Special Topics - - - Statistical Decision Theory; Operations Research

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  1. Heidergott, B. & Leahu, H., 2008. "Differentiability of Product Measures," Serie Research Memoranda 0005, VU University Amsterdam, Faculty of Economics, Business Administration and Econometrics. [Downloadable!]
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This page was last updated on 2009-12-10.


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