Stochastic programming methods applied to network optimization

Authors:
Xian Liu;Yupo Chan;Wilsun Xu
Affiliations:
Department of Systems Engineering, University of Arkansas at Little Rock, Little Rock, AR;Department of Systems Engineering, University of Arkansas at Little Rock, Little Rock, AR;Department of Electrical and Computer Engineering, University of Alberta, Edmonton, AB, Canada
Venue:
Performance Evaluation
Year:
2006

Citing 6
Cited 0

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Abstract

As communication technologies evolve, it becomes necessary to incorporate the stochastic effect of traffic flows into network models. This paper introduces the stochastic programming (SP) methodology for characterizing traffic. Two SP approaches, here-and-now (HN) and scenario tracking (ST), are described through case studies for a prototype network. A numerical optimization procedure is used to perform the simulation. It is clearly demonstrated that when the probability distributions can be estimated analytically, the HN approach can be attractive. Otherwise, the ST approach may be more appropriate.