By António J. M. Castro
Most of the learn efforts facing airline scheduling were performed on off-line plan optimization. despite the fact that, these days, with the more and more advanced and large site visitors at airports, the genuine problem is the best way to react to unforeseen occasions which can reason plan-disruptions, resulting in flight delays.
Moreover those disruptive occasions often impact at the very least 3 assorted dimensions of the placement: the plane assigned to the flight, the workforce project and infrequently forgotten, the passengers’ trip and satisfaction.
This e-book contains solutions to this problem and proposes using the Multi-agent procedure paradigm to quickly compose a multi-faceted approach to the disruptive occasion taking into account 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 alternative software services and never less significant, the inclusion of the human within the computerized decision-making loop make MASDIMA, the process defined during this booklet, well matched for real-life plan-disruption administration applications.
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Additional info for A New Approach for Disruption Management in Airline Operations Control
2 Multi-Agent Systems A Multi-Agent System (MAS) is, typically, a software system composed of multiple interacting intelligent agents (simple agents from now on) within an environment. , an environment where the agents can enter and leave freely, or not, respectively. , 2008)). , a software agent is built that will allow the physical entity to interact with the other agents in the MAS. According to usual agents’ classification methods, we may identify different types of agents. For example, and considering their behavior, the agents can be reactive (perceiving the environment and immediately reacting to changes in it), pro-active (exhibiting goal-directed behavior by taking the initiative to satisfy their design goals) and social (interact with other agents in order to satisfy their goals).
More recently, (Dimopoulos & Moraitis, 2010) updated this information. Regarding game-theory, (Brams, 2003) also provides a good survey on the same subject. We also left out proposals related to generic automated negotiators or frameworks that include tools allowing to design several types of negotiation models including protocols and agent’s strategies, since it is more difficult to compare due to the variety of protocols and agents that can be designed. For example, (Bartolini & Preist, 2001) proposed a framework that supports several models of negotiation for market-based mechanisms.
It is not our intention in this section to do an exhaustive search and comparison between all the existing works. Since we use automated negotiation in our study, our intention is to give the reader a brief characterization of most negotiation protocols together with a brief comparison of what researchers are doing regarding this subject. Before proceeding it is important to provide some definitions as follows. 1. e, that use some kind of learning mechanism. For example, to learn how to formulate new proposals.
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