Minimizing airport peaks problem by improving airline operations performance through an agent based system

• Tipo: Artigo em Livro de Atas de Conferência Internacional
• Data: 2009

Autores

António J. M. Castro (Autor) FEUP; António Mota (Autor) Outra; Luís Paulo Reis (Autor) FEUP; Eugénio Oliveira (Autor) FEUP

Ata de Conferência Internacional

Título: Progress in Artificial Intelligence: Proceedings of the 14th Portuguese Conference on Artificial Intelligence, EPIA2009

Páginas: 3-14

14th EPIA - Portuguese Conference on Artificial Intelligence - EPIA 2009

Universidade de Aveiro, Portugal, 12 a 15 de Outubro de 2009

Classificação Científica

FOS: Ciências exactas e naturais > Ciências da computação e da informação

CORDIS: Ciências Tecnológicas > Tecnologia > Tecnologia do conhecimento

Outras Informações

ID Authenticus: P-011-32X

Abstract (EN): Airports are important infra-structures for the air transportation business. One of the major operational constraints is the peak of passengers in specific periods of time. Airline companies take into consideration the airport capacity when building the airline schedule and, because of that, the execution of the airline operational plan can contribute to improve or avoid airport peak problems. The Airline Operations Control Center (AOCC) tries to solve unexpected problems that might occur during the airline operation. Problems related to aircrafts, crewmembers and passengers are common and the actions towards the solution of these problems are usually known as operations recovery. In this paper we propose a way of measuring the AOCC performance that takes into consideration the relation that exists between airline schedule and airport peaks. The implementation of a Distributed Multi-Agent System (MAS) representing the existing roles in an AOCC, is presented. We show that the MAS contributes to minimize airport peaks without increasing the operational costs of the airlines.

Idioma: Inglês

Tipo (Avaliação Docente): Científica

Nº de páginas: 12