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A multi-agent simulation system for prediction and scheduling of aero engine overhaul

Published: 12 May 2008 Publication History

Abstract

The Aero Repair and Overhaul industry is facing an increasing challenge of prediction and scheduling of engine over-hauls to remain competitive in a complex business arena. An appropriate technology solution is required to achieve efficient schedules while satisfying multiple opposing constraints in a highly dynamic environment. In this paper, we describe Overhaul Prediction and Scheduling, an agent-based simulator developed to tackle this challenge. Using negotiation strategies, it deals with the multi-dimensional scheduling optimisation problem by trading off repair costs, capacity and capability of overhaul bases, among others, in light of in-service unforseen events. It supports effective strategic decision-making via business scenario modelling.

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Cited By

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  • (2018)Life-cycle engine fleet simulation for spare part inventory management with advanced condition informationProceedings of the 2018 Winter Simulation Conference10.5555/3320516.3320792(2309-2320)Online publication date: 9-Dec-2018
  • (2017)A multi-unit combinatorial auction based approach for decentralized multi-project schedulingAutonomous Agents and Multi-Agent Systems10.1007/s10458-017-9370-z31:6(1548-1577)Online publication date: 1-Nov-2017
  • (2016)Decentralized Multi-Project Scheduling via Multi-Unit Combinatorial AuctionProceedings of the 2016 International Conference on Autonomous Agents & Multiagent Systems10.5555/2936924.2937046(836-844)Online publication date: 9-May-2016
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  1. A multi-agent simulation system for prediction and scheduling of aero engine overhaul

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    Published In

    cover image ACM Conferences
    AAMAS '08: Proceedings of the 7th international joint conference on Autonomous agents and multiagent systems: industrial track
    May 2008
    140 pages

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    International Foundation for Autonomous Agents and Multiagent Systems

    Richland, SC

    Publication History

    Published: 12 May 2008

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    Author Tags

    1. aero repair and overhaul
    2. multi-agent systems
    3. negotiation
    4. risk estimation
    5. scheduling
    6. simulation

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    Overall Acceptance Rate 1,155 of 5,036 submissions, 23%

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    Cited By

    View all
    • (2018)Life-cycle engine fleet simulation for spare part inventory management with advanced condition informationProceedings of the 2018 Winter Simulation Conference10.5555/3320516.3320792(2309-2320)Online publication date: 9-Dec-2018
    • (2017)A multi-unit combinatorial auction based approach for decentralized multi-project schedulingAutonomous Agents and Multi-Agent Systems10.1007/s10458-017-9370-z31:6(1548-1577)Online publication date: 1-Nov-2017
    • (2016)Decentralized Multi-Project Scheduling via Multi-Unit Combinatorial AuctionProceedings of the 2016 International Conference on Autonomous Agents & Multiagent Systems10.5555/2936924.2937046(836-844)Online publication date: 9-May-2016
    • (2014)ReviewSignal Processing10.1016/j.sigpro.2013.12.02699(215-249)Online publication date: 1-Jun-2014
    • (2011)Scenario description language in multi-agent simulation systemProceedings of the 5th KES international conference on Agent and multi-agent systems: technologies and applications10.5555/2023144.2023167(169-179)Online publication date: 29-Jun-2011
    • (2010)Convergence of probability collectives with adaptive choice of temperature parametersProceedings of the 4th international conference on Learning and intelligent optimization10.5555/1893659.1893679(200-203)Online publication date: 18-Jan-2010
    • (2009)Decentralised dynamic task allocation: a practical gameProceedings of The 8th International Conference on Autonomous Agents and Multiagent Systems - Volume 210.5555/1558109.1558139(915-922)Online publication date: 10-May-2009

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