Autor(es):
António J. M. Castro 
; Eugénio Oliveira
Data: 2011
Identificador Persistente: http://hdl.handle.net/10216/54256
Origem: Repositório Aberto da Universidade do Porto
Assunto(s): Ciências Físicas; Ciência de computadores; Informática
Descrição
The Airline Operations Control Centre (AOCC) of an Airline Company is the organization responsible for monitoring and solving operational problems. It includes teams of human experts specialized in solving problems related with aircraft, crew members and passengers, in a process called disruption management of operations recovery. In this chapter we propose a new concept fro disruption management in this domain. The organization of the AOCC is represented through a Multi-Agent System (MAS), in which the roles that correspond to the most repetitive tasks are performed by intelligent agents. Human experts represented by agents that are able to inteact with them, are also part of this AOCC-MAS. We show the architecture of our AOCC-MAS, including the main costs involved and details about how the system takes decisions. We tested the concept, using several real airline crew related problems and using four methods: human experts (traditional way), the AOCC-MAS with and without the use of quality-costs and, finally, the integrated approach presented in this chapter. Results are here presented and discussed. The Airline Operations Control Centre (AOCC) of an Airline Company is the organization responsible for monitoring and solving operational problems. It includes teams of human experts specialized in solving problems related with aircraft, crew members and passengers, in a process called disruption management of operations recovery. In this chapter we propose a new concept fro disruption management in this domain. The organization of the AOCC is represented through a Multi-Agent System (MAS), in which the roles that correspond to the most repetitive tasks are performed by intelligent agents. Human experts represented by agents that are able to inteact with them, are also part of this AOCC-MAS. We show the architecture of our AOCC-MAS, including the main costs involved and details about how the system takes decisions. We tested the concept, using several real airline crew related problems and using four methods: human experts (traditional way), the AOCC-MAS with and without the use of quality-costs and, finally, the integrated approach presented in this chapter. Results are here presented and discussed.
