Tradable credit scheme (TCS) is a novel quantity-based traffic demand management (TDM) instrument, which performs better than road congestion pricing in terms of social equity and revenue neutrality. To analyze the potentials of TCS to improve the sustainable development level of a transportation network, this paper investigates the optimal tradable credit scheme (TCS) design problem at network-wide level, aiming at improving system efficiency, fuel economy and low-emission simultaneously. In order to evaluate these three indicators under a given TCS in an integrated way, we combine them into a sustainable development index (SDI) via a linear combination. Then a bi-level programming model is established for the multi-objective optimal TCS design problem, of which the upper level problem is the optimal TCS design problem to maximize the SDI from the viewpoint of traffic managers, and the lower level problem is the stochastic user equilibrium (SUE) assignment problem under TCS to capture travelers’ route choice behavior under a given TCS. Finally, a combined genetic algorithm and Lagrangian dual method (GA-LDM) is used to solve the bi-level optimization model, with the LDM solving the SUE model with TCS in the lower level. In order to verify the proposed model and algorithm, the classical Nguyen-Dupuis network is taken as the numerical example, and the numerical results show that the model and algorithm are effective and efficient.

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