Abstract
A multi-objective freight train routing problem with fuzzy information is investigated in this article. To handle the fuzziness in the railway transportation system, the measure ℳλ (i.e. the convex combination of a possibility measure and a necessity measure) is first introduced. Then, a min–max chance-constrained programming model is constructed to obtain optimal train routing plans. In order to solve the model, a potential route algorithm, fuzzy simulation and tabu search algorithm are integrated as a hybrid algorithm. Finally, some numerical experiments are performed to show the applications of the model and the algorithm.
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