By António J. M. Castro
Most of the examine efforts facing airline scheduling were performed on off-line plan optimization. besides the fact that, these days, with the more and more complicated and large site visitors at airports, the genuine problem is the right way to react to unforeseen occasions which may reason plan-disruptions, resulting in flight delays.
Moreover those disruptive occasions frequently have an effect on not less than 3 diversified dimensions of the placement: the plane assigned to the flight, the team project and sometimes forgotten, the passengers’ trip and satisfaction.
This e-book comprises solutions to this problem and proposes using the Multi-agent method paradigm to swiftly compose a multi-faceted way to the disruptive occasion making an allowance for 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, blend of alternative software services and never less significant, the inclusion of the human within the computerized decision-making loop make MASDIMA, the approach defined during this publication, like minded for real-life plan-disruption administration applications.
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Additional resources for A New Approach for Disruption Management in Airline Operations Control
Sixth Observation The information system available for the users in the AOCC that have to find solutions to the problems, provides only operational information, that is, information that is necessary for the operation to be performed (for example, aircraft status and maintenance, crew data related with licenses, qualifications and roster). 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.
This includes description of the attributes under negotiation as well as the constants that represent the negotiation attributes’ value and any other needed descriptor symbols. Efforts have been made to provide standard domain languages that can be used by agents in heterogeneous environments . For example, DML-DARPA Agent Markup Language (Hendler & McGuiness, 2000) and W3C Web Ontology Language (OWL) (McGuiness & van Harmelen, 2003). , a conversation. There are dozens of interaction protocols for agent-based systems, making it impossible to mention all of them here.
2, respectively, show how we have applied these algorithms to this problem. The passenger problem dimension is different from the aircraft and crew’s. It can easily be modeled as a shortest path problem, since the objective is to find the least costing path for each passenger to reach his destination airport from a starting airport. 3 shows how we have applied the Dijkstra’s algorithm to this problem. 6 Chapter Summary The objective of this chapter was twofold: • Provide some brief information regarding some of the paradigms, concepts and algorithms we will use later on in our work description, specifically, the MultiAgent System, Problem Solving Algorithms and Reinforcement Learning.