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Stochastic Networks: Modeling, Simul...

Li, Juan.

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Stochastic Networks: Modeling, Simulation Design and Risk Control.

紀錄類型:	書目-電子資源 : Monograph/item
正題名/作者:	Stochastic Networks: Modeling, Simulation Design and Risk Control./
作者:	Li, Juan.
面頁冊數:	172 p.
附註:	Source: Dissertation Abstracts International, Volume: 77-03(E), Section: B.
Contained By:	Dissertation Abstracts International77-03B(E).
標題:	Operations research. -
電子資源:	http://pqdd.sinica.edu.tw/twdaoapp/servlet/advanced?query=3729344
ISBN:	9781339151151

Stochastic Networks: Modeling, Simulation Design and Risk Control.
Li, Juan.

Stochastic Networks: Modeling, Simulation Design and Risk Control. - 172 p.

Source: Dissertation Abstracts International, Volume: 77-03(E), Section: B.

Thesis (Ph.D.)--Columbia University, 2015.

This dissertation studies stochastic network problems that arise in various areas with important industrial applications. Due to uncertainty of both external and internal variables, these networks are exposed to the risk of failure with certain probability, which, in many cases, is very small. It is thus desirable to develop efficient simulation algorithms to study the stability of these networks and provide guidance for risk control.

ISBN: 9781339151151Subjects--Topical Terms:

547123
Operations research.

Stochastic Networks: Modeling, Simulation Design and Risk Control.
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245 1 0 $a Stochastic Networks: Modeling, Simulation Design and Risk Control.
300 $a 172 p.
500 $a Source: Dissertation Abstracts International, Volume: 77-03(E), Section: B.
500 $a Adviser: Jose Blanchet.
502 $a Thesis (Ph.D.)--Columbia University, 2015.
520 $a This dissertation studies stochastic network problems that arise in various areas with important industrial applications. Due to uncertainty of both external and internal variables, these networks are exposed to the risk of failure with certain probability, which, in many cases, is very small. It is thus desirable to develop efficient simulation algorithms to study the stability of these networks and provide guidance for risk control.
520 $a Chapter 2 models equilibrium allocations in a distribution network as the solution of a linear program (LP) which minimizes the cost of unserved demands across nodes in the network. Assuming that the demands are random (following a jointly Gaussian law), we study the probability that the optimal cost exceeds a large threshold, which is a rare event. Our contribution is the development of importance sampling and conditional Monte Carlo algorithms for estimating this probability. We establish the asymptotic efficiency of our algorithms and also present numerical results that demonstrate the strong performance of our algorithms.
520 $a Chapter 3 studies an insurance-reinsurance network model that deals with default contagion risks with a particular aim of capturing cascading effects at the time of defaults. We capture these effects by finding an equilibrium allocation of settlements that can be found as the unique optimal solution of an optimization problem. We are able to obtain an asymptotic description of the most likely ways in which the default of a specific group of participants can occur, by solving a multidimensional Knapsack integer programming problem. We also propose a class of strongly efficient Monte Carlo estimators for computing the expected loss of the network conditioned on the failure of a specific set of companies.
520 $a Chapter 4 discusses control schemes for maintaining low failure probability of a transmission system power line. We construct a stochastic differential equation to describe the temperature evolution in a line subject to stochastic exogenous factors such as ambient temperature, and present a solution to the resulting stochastic heat equation. A number of control algorithms designed to limit the probability that a line exceeds its critical temperature are provided.
590 $a School code: 0054.
650 4 $a Operations research. $3 547123
650 4 $a Engineering. $3 586835
650 4 $a Finance. $3 542899
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710 2 $a Columbia University. $b Operations Research. $3 2096452
773 0 $t Dissertation Abstracts International $g 77-03B(E).
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792 $a 2015
793 $a English
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