Expert Systems with Applications: An International Journal
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Multimodal transportation is a complex network, in which all the components should be seamlessly linked and efficiently coordinated. Considered many noncommensurable, nonlinear even conflicting criteria simultaneously, the transport mode selection in multimodal transportation is studied within the framework of multicriteria decision making (MCDM). The theoretical basis for feedforward artificial neural network (FANN) to solve this MCDM problem is presented. With the initial topology predetermined by fuzzy analysis hierarchy process (AHP), an adaptive ANN system is proposed, in which the number of ANN input nodes adapts the decision makers’ preference threshold and the initial input weights are determined by fuzzy AHP. Empirical results evidently show this MCDM method is an accurate, flexible and efficient transport mode selection model.