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Urban transport traffic network regulation and evaluation using a fuzzy evolutionary approach

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The real-time regulation of urban collective transport traffic is a very delicate problem, particularly in case of appearance of simultaneous disturbances (vehicle's breakdown, strike, demonstration, etc.). Indeed, a regulator (a decision maker) has to carry out difficult tasks that are often inaccessible at the human scale and involve the assistance of a decision support system (DSS). In this paper, we present the main part of this DSS, i.e., the generator and the evaluator of the decision strategies for disrupted transport network regulation. The proposed module is based on a hybrid approach using a fuzzy evaluation method and evolutionary algorithms. It treats the online regulation problem as an optimization one and provides the regulator with evaluated and classified effective decisions by taking into account his/her preferences.

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