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Title: Joint optimization of logistics infrastructure investments and subsidies in a regional logistics network with CO 2 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. In conclusion, carbon emission reduction targets can significantly affect logistics infrastructure investments and subsidy levels.

Authors:
 [1];  [1];  [2];  [3]
  1. Central South Univ., Hunan (China)
  2. National Renewable Energy Lab. (NREL), Golden, CO (United States)
  3. Central South Univ. of Forestry and Technology, Hunan (China)
Publication Date:
Research Org.:
National Renewable Energy Lab. (NREL), Golden, CO (United States)
Sponsoring Org.:
USDOE Office of Energy Efficiency and Renewable Energy (EERE)
OSTI Identifier:
1395095
Alternate Identifier(s):
OSTI ID: 1556160
Report Number(s):
NREL/JA-5400-66201
Journal ID: ISSN 1361-9209
Grant/Contract Number:  
AC36-08GO28308
Resource Type:
Accepted Manuscript
Journal Name:
Transportation Research. Part D, Transport and Environment
Additional Journal Information:
Journal Volume: 60; Journal ID: ISSN 1361-9209
Publisher:
Elsevier
Country of Publication:
United States
Language:
English
Subject:
29 ENERGY PLANNING, POLICY, AND ECONOMY; regional logistics network; bi-level model; logistics infrastructure investment; subsidies for green transport modes; CO2 emission reduction target

Citation Formats

Zhang, Dezhi, Zhan, Qingwen, Chen, Yuche, and Li, Shuangyan. Joint optimization of logistics infrastructure investments and subsidies in a regional logistics network with CO2 emission reduction targets. United States: N. p., 2016. Web. doi:10.1016/j.trd.2016.02.019.
Zhang, Dezhi, Zhan, Qingwen, Chen, Yuche, & Li, Shuangyan. Joint optimization of logistics infrastructure investments and subsidies in a regional logistics network with CO2 emission reduction targets. United States. doi:10.1016/j.trd.2016.02.019.
Zhang, Dezhi, Zhan, Qingwen, Chen, Yuche, and Li, Shuangyan. Mon . "Joint optimization of logistics infrastructure investments and subsidies in a regional logistics network with CO2 emission reduction targets". United States. doi:10.1016/j.trd.2016.02.019. https://www.osti.gov/servlets/purl/1395095.
@article{osti_1395095,
title = {Joint optimization of logistics infrastructure investments and subsidies in a regional logistics network with CO2 emission reduction targets},
author = {Zhang, Dezhi and Zhan, Qingwen and Chen, Yuche and Li, Shuangyan},
abstractNote = {This study proposes an optimization model that simultaneously incorporates the selection of logistics infrastructure investments and subsidies for green transport modes to achieve specific CO2 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. In conclusion, carbon emission reduction targets can significantly affect logistics infrastructure investments and subsidy levels.},
doi = {10.1016/j.trd.2016.02.019},
journal = {Transportation Research. Part D, Transport and Environment},
number = ,
volume = 60,
place = {United States},
year = {2016},
month = {3}
}

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Works referencing / citing this record:

Multi-objective model for optimizing railway infrastructure asset renewal
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