Optimizing decision-making of regional cold chain logistics system in view of low-carbon economy

With the increasing demand for low-carbon cold chain logistics, corresponding subsidy policy and carbon emissions trading policy are needed to guide cold chain logistics enterprises in energy-saving and emission reduction transformation of cold storage. However, current research mainly focuses on energy-saving and emission reduction through improving the energy efficiency of equipment or optimizing the operation and management of cold chain logistics enterprises, rarely considering the government policy. This paper constructs a decision-making model of cold chain logistics system by using the method of bilevel programming. The upper level is the government's goal, pursuing the total cost minimization of the whole cold chain logistics system. The lower level is the goal of the cold chain logistics enterprise, pursuing the cost minimization of the enterprise. Chaotic particle swarm optimization (CPSO) was developed to improve this model, and this method was applied to the decision-making of cold chain logistics system in Wuhan City, Hubei Province, China. The study reveals: (1) The joint use of carbon emission reduction subsidies and carbon emission quota optimization measures is more effective in promoting energy-saving and emission reduction of enterprises than using them separately; (2) The carbon emission quota set by the government should not be too high or too low; (3) The government subsidy limits for carbon emission reduction have a significant impact on the carbon emission reduction of enterprises; (4) The subsidy rate per unit carbon emission reduction can adjust the total carbon emissions and total carbon emission reduction of enterprises. This study provides a scientific basis and inspires the government and enterprise in decision-making to improve the energy-saving and emission reduction of the whole society.

• Record URL:
  https://doi.org/10.1016/j.tra.2019.10.004
• Record URL:
  http://www.sciencedirect.com/science/article/pii/S0965856419306779
• Availability:
  • Find a library where document is available. Order URL: http://worldcat.org/issn/09658564
• Supplemental Notes:
  • © 2019 Elsevier Ltd. All rights reserved. Abstract reprinted with permission of Elsevier.
• Authors:
  • Zhang, Siying
  • Chen, Ning
  • Song, Xiaoming
  • Yang, Jia
• Publication Date: 2019-12

Language

• English

Media Info

• Media Type: Web
• Features: Appendices; Figures; References; Tables;
• Pagination: pp 844-857
• Serial:
  • Transportation Research Part A: Policy and Practice
  • Volume: 130
  • Issue Number: 0
  • Publisher: Elsevier
  • ISSN: 0965-8564
  • Serial URL: http://www.sciencedirect.com/science/journal/09658564

Subject/Index Terms

• TRT Terms: Decision making; Emissions trading; Energy consumption; Logistics; Low temperature; Optimization; Pollutants; Programming (Mathematics); Subsidies; Supply chain management
• Geographic Terms: Wuhan (China)
• Subject Areas: Economics; Environment; Freight Transportation; Planning and Forecasting;

Filing Info

• Accession Number: 01723665
• Record Type: Publication
• Files: TRIS
• Created Date: Nov 26 2019 10:19AM