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Multiobjective optimum path algorithm for passenger pretrip planning in multimodal transportation networks Aifadopoulou, Georgia ; Ziliaskopoulos, Athanasios ; Chrisohoou, Evangelia

By: Contributor(s): Series: ; 2032Publication details: Transportation research record, 2007Description: s. 26-34Subject(s): Bibl.nr: VTI P8167:2032Location: Abstract: This paper aims to present a multiobjective optimum path algorithm for passenger pretrip planning in multimodal transportation networks. The process of identifying the feasible paths accounts for the delays caused by the different modes and the terminal switching. This algorithm is designed to constitute a component of an integrated web-based information gateway, aiming to provide information to travelers through the Internet for intercity trips using public transport. The algorithm identifies feasible paths according to compatibility of various modes, intermodal stations, and users' preferences. The multiobjective linear programming model that corresponds to this process is presented to prove the efficiency of the algorithm. An implementation for the proposed algorithm is designed, coded, and computationally tested in realistic-size networks. The computational complexity of the algorithm is proven to be polynomial.
Item type: Reports, conferences, monographs
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Statens väg- och transportforskningsinstitut Available

This paper aims to present a multiobjective optimum path algorithm for passenger pretrip planning in multimodal transportation networks. The process of identifying the feasible paths accounts for the delays caused by the different modes and the terminal switching. This algorithm is designed to constitute a component of an integrated web-based information gateway, aiming to provide information to travelers through the Internet for intercity trips using public transport. The algorithm identifies feasible paths according to compatibility of various modes, intermodal stations, and users' preferences. The multiobjective linear programming model that corresponds to this process is presented to prove the efficiency of the algorithm. An implementation for the proposed algorithm is designed, coded, and computationally tested in realistic-size networks. The computational complexity of the algorithm is proven to be polynomial.