A New Approach for Disruption Management in Airline by António J. M. Castro

By António J. M. Castro

Most of the examine efforts facing airline scheduling were performed on off-line plan optimization. even though, these days, with the more and more advanced and enormous site visitors at airports, the true problem is tips on how to react to unforeseen occasions which may reason plan-disruptions, resulting in flight delays.

Moreover those disruptive occasions frequently have an effect on at the least 3 diverse dimensions of the location: the plane assigned to the flight, the workforce task and sometimes forgotten, the passengers’ trip and satisfaction.

This ebook comprises solutions to this problem and proposes using the Multi-agent method paradigm to swiftly compose a multi-faceted approach to the disruptive occasion bearing in mind attainable personal tastes of these 3 key facets of the problem.

Negotiation protocols happening among brokers which are specialists in fixing the several challenge dimensions, mix of other software features and never less significant, the inclusion of the human within the automated decision-making loop make MASDIMA, the approach defined during this ebook, like minded for real-life plan-disruption administration applications.

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The protocol is verified by the TRACONET (TRAnsportation COoperation NET) system presented in the paper, where dispatch centers of different companies cooperate automatically in vehicle routing. , during bid formulation the agents propose, in one shot, a lower value than the one (representing the cost so far) received in the announcement. Additionally, the agents need to have full knowledge to make a bid. , 2004). Like in the previous work, it allows competitive and cooperative agents supporting solutions taking only a single dimension in consideration.

Team members can have access to airport information or weather information, for example, but not in an integrated way. They need to use different computer systems for that. 2 Hypotheses Having the observations we have formulated the following hypotheses. , to distribute the data and the roles. It also allows to achieve the functional distribution identified in the second observation, by distributing the roles by agents according to the dimensions of the problem, required expertise and contemplating the individual goals and preferences.

2004) Bil. 1-M (Dang & Huhns, 2005) Bil. , 2005, 2004, 2002) Multil. 1-M (Goradia, 2007) Multil. , 2007) Bil. 1-M (Crawford & Veloso, 2008) Bil. 1-M (Jain & Deshmukh, 2009) Bil. 1-M (Katsuhide Fujita & Klein, 2010) Multil. M-M Our Proposal (GQN) Bil. 1-M Knwl Env. S F M F M F M F M-Interd. F S F M F M F S F/P M F S F M-Interd. F M-Interd. F M-Interd. F/P Adap. Mixed No Comp. Yes Comp. Yes Comp. No S-comp. No Mixed No Comp. No Mixed No Comp. No Comp. No S-coop. Yes Mixed Yes Mixed No Mixed Yes & Sycara, 1998) proposes a negotiation protocol with a sequential decision making model called Bazaar.

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