Detection and improvement of deficiencies and failures in public-transportation networks using agent-enhanced distribution data mining

Abstract

The main goal of this paper is to develop a general methodology for both pinpointing the weak elements of public transportation (PT) systems and finding least-cost solutions for improvements. The methodology is based on network routing, scheduling, and real-time control algorithms. These algorithms detect deficiencies and failures of the PT network and in operations planning. The main practical objective and challenge of this work is to provide a decision-support system for the prognosis and detection of the deficiencies of the PT network and measures required to their remedy. The system is based on off- and online algorithms and methods associated with multi-agent systems.

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