Demand-responsive transport services are systems that assign users ’ specific transport requests to different vehicles enabled to fulfill the required service. In order to contain costs, maximize profits or get a higher service level, different planning algorithms have been described in literature. In our work we propose a multi-agent architecture, which adopts a mixed planning model. This model is an integration of centralized and negotiation based decision-making approaches. The advantage of using this model respect to a centralized approach is that the estimation of the uti1ir) function is avoided (the client is involved in the final decision by means of a negotiation process). The model advantages a complete decentralized approach in giving results that are not so far from the optimum for the whole system.
Multi-agent infrastructure for distributed planning of demand-responsive passenger transportation service / Claudio, Cubillos; FRANCO GUIDI POLANCO, And; Demartini, Claudio Giovanni. - (2004), pp. 2013-2017. (Intervento presentato al convegno Proceedings of the IEEE International Conference on Systems, tenutosi a The Hague, Netherlands nel 10-13 October, 2004).
Multi-agent infrastructure for distributed planning of demand-responsive passenger transportation service
DEMARTINI, Claudio Giovanni
2004
Abstract
Demand-responsive transport services are systems that assign users ’ specific transport requests to different vehicles enabled to fulfill the required service. In order to contain costs, maximize profits or get a higher service level, different planning algorithms have been described in literature. In our work we propose a multi-agent architecture, which adopts a mixed planning model. This model is an integration of centralized and negotiation based decision-making approaches. The advantage of using this model respect to a centralized approach is that the estimation of the uti1ir) function is avoided (the client is involved in the final decision by means of a negotiation process). The model advantages a complete decentralized approach in giving results that are not so far from the optimum for the whole system.File | Dimensione | Formato | |
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https://hdl.handle.net/11583/1643722
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