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

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. Carbon emission reduction targets can significantly affect logistics infrastructure investments and subsidy levels.

• Record URL:
  https://doi.org/10.1016/j.trd.2016.02.019
• Record URL:
  http://www.sciencedirect.com/science/article/pii/S1361920916000286
• Availability:
  • Find a library where document is available. Order URL: http://worldcat.org/issn/13619209
• Supplemental Notes:
  • Abstract reprinted with permission of Elsevier.
• Authors:
  • Zhang, Dezhi
  • Zhan, Qingwen
  • Chen, Yuche
  • Li, Shuangyan
• Publication Date: 2018-6

Language

• English

Media Info

• Media Type: Web
• Features: Figures; References; Tables;
• Pagination: pp 174-190
• Serial:
  • Transportation Research Part D: Transport and Environment
  • Volume: 60
  • Issue Number: 0
  • Publisher: Elsevier
  • ISSN: 1361-9209
  • Serial URL: http://www.sciencedirect.com/science/journal/13619209

Subject/Index Terms

• TRT Terms: Carbon dioxide; Genetic algorithms; Infrastructure; Investments; Logistics; Optimization; Pollutants; Regional transportation; Sustainable transportation
• Geographic Terms: Changsha (China)
• Subject Areas: Environment; Finance; Freight Transportation; Planning and Forecasting;

Filing Info

• Accession Number: 01666322
• Record Type: Publication
• Files: TRIS
• Created Date: Apr 19 2018 10:02AM