A Multi-Agent System for Airline Operations Control

Castro,; Oliveira, Eugénio

doi:10.1007/978-3-642-00487-2_17

Cited by 6 publications

(6 citation statements)

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“…Although we could just list the requirements of the system-to-be, taken from interviews from the stakeholders and users, we think it is important to have a better understanding of those requirements early in the process. For the MAS we have developed for the airline company (Castro and Oliveira, 2005), we choose to adopt a goal-oriented early requirements analysis. The choice was to follow the early requirements analysis of Tropos (Bresciani et al, 2004).…”

Section: A Goal-oriented Early Requirements Analysismentioning

confidence: 99%

The rationale behind the development of an airline operations control centre using Gaia-based methodology

Castro

Oliveira

2008

IJAOSE

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Abstract:In this paper, we report how we complemented Gaia methodology to analyse and design a multi-agent system for an airline company operations control centre. Besides showing the rationale behind the analysis, design and implementation of our system, we also present how we mapped the abstractions used in agent-oriented design to specific constructs in JADE. The advantages of using a goal-oriented early requirements analysis and its influence on subsequent phases of analysis and design are also presented. Finally, we also propose UML 2.0 diagrams at several different levels for the representation of Gaia deliverables, such as organisational structure, role and interaction model, and agent and service model. Keywords: multi-agent systems; agent-oriented methodologies; goal-oriented requirements analysis; operations recovery; disruption management.Reference to this paper should be made as follows: Castro, A. and Oliveira, E. (2008) 'The rationale behind the development of an airline operations control centre using Gaia-based methodology', Int. J. Vol. 2, No. 3, Biographical notes: António Castro is a Software Engineer at TAP Portugal, the Portuguese airline company, where he manages software projects related to crew scheduling and operations control. He is currently a PhD student of Informatics Engineering at the Faculty of Engineering, University of Porto. His current research interests include multi-agent systems, agent-oriented software engineering and distributed systems. The rationale behind the development of an airline OCC 351Eugénio Oliveira is a Full Professor at the University of Porto, Portugal. He coordinates a research group on distributed artificial intelligence in the LIACC Lab and a doctoral programme in informatics. He obtained his PhD in Knowledge Engineering/Logic Programming from the Universidade Nova in Lisbon (1984). He was Guest Academic at IBM/IEC, Belgium (1984Belgium ( -1985. He was awarded the Gulbenkian Prize in 1983. He has participated in European and nationally funded projects involving intelligent agents. Agent-based frameworks for B2B, multi-agent learning and agent-based teamwork are current topics of interest. He has published a number of papers in journals and proceedings.

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Section: A Goal-oriented Early Requirements Analysismentioning

confidence: 99%

The rationale behind the development of an airline operations control centre using Gaia-based methodology

Castro

Oliveira

2008

IJAOSE

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“…The MAS was developed using JADE (Bellifemine et al, 2004) as development platform and as the run-time environment that provides the basic services for agents to execute. The MAS was developed based on a previous analysis and design by Castro and Oliveira (Castro and Oliveira, 2005).…”

Section: General Descriptionmentioning

confidence: 99%

A Distributed Multi-Agent System to Solve Airline Operations Problems

Castro

Oliveira

2007

Proceedings of the Ninth International Conference on Enterprise Information Systems

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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 or disruption management. The Airline Operations Control Center (AOCC) tries to solve these problems with the minimum impact in the airline schedule, with the minimum cost and, at the same time, satisfying all the required safety rules. Usually, each problem is treated separately and some tools have been proposed to help in the decision making process of the airline coordinators. In this paper we present the implementation of a Distributed Multi-Agent System (MAS) that represents the several roles that exist in an AOCC. This MAS deals with several operational bases and for each type of operation problems it has several specialized software agents that implements heuristic solutions and other solutions based in operations research mathematic models and artificial intelligence algorithms. These specialized agents compete 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 using the MAS. 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 Airline Operations Control Center. We show that, even in simple problems and when comparing with solutions found by human operators in the case of this airline company, it is possible to find valid solutions, in less time and with a smaller cost.

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“…[41][42][43][44][45][46][47][48] The implication of agent technology to various evolution directions related to smart transportation is demonstrated by the broad application of academic and industrial research results. Some examples include urban traffic management, [49][50][51] planning, operation, and control of transport systems, 1,52,53 staff scheduling and rostering and resource allocation for public transport service delivery, [54][55][56] design of intelligent vehicles that act as agents in an information integrated network, 57 empowering transport service customers with information about their transportation choices, 26,58 or evaluation of environmental impact of transportation modes. 5 The case study presented in this paper approaches the development of improved service offerings in a public transport service company.…”

Section: Introductionmentioning

confidence: 99%

Service interactions modeling for improved management of public transport systems

2016

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This paper shows how service science principles may be used for engineering and realizing improved public transport services. It approaches a value co-creation perspective for the management of public transport service operations based on an activity-based model of a generic service system that allows capturing requirements for software intensive service systems. The main focus is on specific implementation issues of the activity-based model of the generic service system, with a strong accent on its most representative component, the service set-up and configuring unit. This model is applied in a case study for planning of a public transport service and describes how a specific service reconfiguring request is formulated. This examination is further used as a document of requirements that drives the construction of an agent-based model expressing value-creation interactions among service system’s stakeholders in public transport services. The usefulness of the developed agent-based model for the analysis of service systems operational capabilities is suggested through simulation. A business scenario related to the management of public transport services is described, and the defined agent-based model is executed with the Presage2 multi-agent programming platform in order to capture specific issues of piece-of-work planning. The proposed approach, evaluated on the simple working scenario, fosters the role of service interaction modeling in supporting a public transport service system to dynamically adapt its operational capabilities in delivering good public transport services, as more or less quantifiable changes can affect service delivery over time.

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A Multi-Agent System for Airline Operations Control

Cited by 6 publications

References 10 publications

The rationale behind the development of an airline operations control centre using Gaia-based methodology

The rationale behind the development of an airline operations control centre using Gaia-based methodology

A Distributed Multi-Agent System to Solve Airline Operations Problems

Service interactions modeling for improved management of public transport systems

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