An Asymmetric Intelligent Model for Public Transportation Networks

This paper proposes an asymmetric model for urban public transportation networks. Predictive techniques are being developed, to allow advanced modeling and comparison with historical baseline data. The current trend is toward fewer costly microprocessor modules with hardware memory management and real-time operating systems. This model is formulated as a linear programming problem using LP-solvers and is developed and simulated for a large metropolitan area of Tehran, Iran. The mathematical procedure as its quantitative results is presented.

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