Solving airline operations problems using specialized agents in a distributed multi-agent system

• Tipo: Artigo em Livro de Atas de Conferência Internacional
• Data: 2008

Autores

António J. M. Castro (Autor) FEUP; Eugénio Oliveira (Autor) FEUP

Ata de Conferência Internacional

Título: Lecture Notes in Business Information Processing (LNBIP) 12 ICEIS 2007

Páginas: 173-184

Enterprise Information Systems: 9th International Conference, ICEIS 2007

Indexação

ISI Web of Knowledge - 0 Citações

Scopus - 0 Citações

Classificação Científica

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

CORDIS: Ciências Físicas > Ciência de computadores > Cibernética > Inteligência artificial

Outras Informações

ID Authenticus: P-004-34N

DOI: 10.1007/978-3-540-88710-2_14

Abstract (EN): An airline schedule very rarely operates as planned. Problems related with aircrafts, crew members and passengers are common and the actions towards the solution of these problems are usually known as operations recovery. The Airline Operations Control Center (AOCC) tries to solve these problems with the minimum cost and satisfying all the required rules. In this paper we present the implementation of a Distributed Multi-Agent System (MAS) representing the existing roles in an AOCC, This MAS deals with several operational bases and for each type of operation problems it has several specialized software agents that implement different algorithms (heuristic, AI, OR, etc.), competing to find the best solution for each problem. We present a real case study taken from an AOCC where a crew recovery problem is solved. Computational results using a real airline schedule are presented, including a comparison with a solution for the same problem found by the human operators in the AOCC. We show that, even in simple problems and when comparing with solutions found by human operators, it is possible to find valid solutions, in less time and with a smaller cost.

Idioma: Inglês

Tipo (Avaliação Docente): Científica

Nº de páginas: 12