Joint optimization of logistics infrastructure investments and subsidies in a regional logistics network with CO2 emission reduction targets

Abstract This study proposes an optimization model that simultaneously incorporates the selection of logistics infrastructure investments and subsidies for green transport modes to achieve specific CO 2 emission targets in a regional logistics network. The proposed model is formulated as a bi-level formulation, in which the upper level determines the optimal selection of logistics infrastructure investments and subsidies for green transport modes such that the benefit–cost ratio of the entire logistics system is maximized. The lower level describes the selected service routes of logistics users. A genetic and Frank–Wolfe hybrid algorithm is introduced to solve the proposed model. The proposed model is applied to the regional logistics network of Changsha City, China. Findings show that using the joint scheme of the selection of logistics infrastructure investments and green subsidies is more effective than using them solely. Carbon emission reduction targets can significantly affect logistics infrastructure investments and subsidy levels.

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