Modeling of an airline operations control center as a queueing network

Pujet Nicolas; Eric Feron; Rakhit Ananda

doi:10.1109/ACC.1998.707326

Modeling of an airline operations control center as a queueing network

Pujet Nicolas, Eric Feron, Rakhit Ananda

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution

4 Scopus citations

Abstract

A discrete event model for multi-agent real-time process control is introduced in the context of United Airlines' Operations Control Center (OCC). The model represents the OCC agents as a network of queuing servers, and organizes the individual communication and decision tasks into discrete event processes flowing through this queuing network. The input to the agent network is the superposition of a deterministic periodic demand, a stochastic demand and an uncertain forecast of future demand. The identification of the dynamic characteristics of each agent in the network is carried out through a combination of on-site measurements and statistical analysis of transactional data. A computer simulation of this OCC model is presented. © 1998 AACC.

Original language	English (US)
Title of host publication	Proceedings of the American Control Conference
Pages	1800-1803
Number of pages	4
DOIs	https://doi.org/10.1109/ACC.1998.707326
State	Published - Dec 1 1998
Externally published	Yes

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10.1109/ACC.1998.707326

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title = "Modeling of an airline operations control center as a queueing network",

abstract = "A discrete event model for multi-agent real-time process control is introduced in the context of United Airlines' Operations Control Center (OCC). The model represents the OCC agents as a network of queuing servers, and organizes the individual communication and decision tasks into discrete event processes flowing through this queuing network. The input to the agent network is the superposition of a deterministic periodic demand, a stochastic demand and an uncertain forecast of future demand. The identification of the dynamic characteristics of each agent in the network is carried out through a combination of on-site measurements and statistical analysis of transactional data. A computer simulation of this OCC model is presented. {\textcopyright} 1998 AACC.",

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year = "1998",

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AU - Feron, Eric

AU - Ananda, Rakhit

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PY - 1998/12/1

Y1 - 1998/12/1

N2 - A discrete event model for multi-agent real-time process control is introduced in the context of United Airlines' Operations Control Center (OCC). The model represents the OCC agents as a network of queuing servers, and organizes the individual communication and decision tasks into discrete event processes flowing through this queuing network. The input to the agent network is the superposition of a deterministic periodic demand, a stochastic demand and an uncertain forecast of future demand. The identification of the dynamic characteristics of each agent in the network is carried out through a combination of on-site measurements and statistical analysis of transactional data. A computer simulation of this OCC model is presented. © 1998 AACC.

AB - A discrete event model for multi-agent real-time process control is introduced in the context of United Airlines' Operations Control Center (OCC). The model represents the OCC agents as a network of queuing servers, and organizes the individual communication and decision tasks into discrete event processes flowing through this queuing network. The input to the agent network is the superposition of a deterministic periodic demand, a stochastic demand and an uncertain forecast of future demand. The identification of the dynamic characteristics of each agent in the network is carried out through a combination of on-site measurements and statistical analysis of transactional data. A computer simulation of this OCC model is presented. © 1998 AACC.

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U2 - 10.1109/ACC.1998.707326

DO - 10.1109/ACC.1998.707326

M3 - Conference contribution

SN - 0780345304

SP - 1800

EP - 1803

BT - Proceedings of the American Control Conference

ER -

Modeling of an airline operations control center as a queueing network

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