Optimization of Long-Run Average-Flow Cost in Networks With Time-Varying Unknown Demand

Dario Bauso, Franco Blanchini, Raffaele Pesenti

Risultato della ricerca: Articlepeer review

17 Citazioni (Scopus)

Abstract

We consider continuous-time robust network flows with capacity constraints and unknown but bounded time-varying demand. The problem of interest is to design a control strategy off-line with no knowledge of the demand realization. Such a control strategy regulates the flow on-line as a function of the realized demand. We address both the case of systems without and with buffers. The main novelty in this work is that we consider a convex cost which is a function of the long-run average-flow and average-demand. We distinguish a worst-case scenario where the demand is the worst-one from a deterministic scenario where the demand has a neutral behavior. The resulting strategies are called min-max or deterministically optimal respectively. The main contribution are constructive methods to design either min-max or deterministically optimal strategies. We prove that while the min-max optimal strategy is memoryless, i.e., it is a piece-wise affine function of the current demand, deterministically optimal strategy must keep memory of the average flow up to the current time.
Lingua originaleEnglish
pagine (da-a)20-31
Numero di pagine11
RivistaIEEE Transactions on Automatic Control
Volume55
Stato di pubblicazionePublished - 2010

All Science Journal Classification (ASJC) codes

  • Control and Systems Engineering
  • Computer Science Applications
  • Electrical and Electronic Engineering

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