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Multi-objective cold chain logistic distribution center location based on carbon emission.

Xinguang Li1, Kang Zhou2

  • 1School of Mechanical and Automobile, Qingdao University of Technology, Qingdao, 266520, China. tutulxg@126.com.

Environmental Science and Pollution Research International
|February 24, 2021
PubMed
Summary

This study optimizes cold chain logistics distribution center location by balancing carbon emissions and customer satisfaction. The developed model and algorithm provide effective Pareto solutions for complex distribution challenges.

Keywords:
Carbon emissionCold chain logisticsCustomer satisfactionDistribution location problem

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Area of Science:

  • Logistics and Supply Chain Management
  • Environmental Science
  • Operations Research

Background:

  • Growing concerns for food safety and environmental protection necessitate efficient cold chain logistics.
  • Cold chain products require continuous refrigeration and timely delivery, posing challenges for emissions reduction and customer satisfaction.
  • Balancing delivery speed, carbon footprint, and costs is crucial for modern distribution networks.

Purpose of the Study:

  • To develop a multi-objective location model for cold chain logistics distribution centers that incorporates carbon emissions.
  • To analyze the impact of carbon emissions, customer satisfaction, construction, and operation costs on distribution center location decisions.
  • To present an efficient optimization algorithm for solving the complex multi-objective problem.

Main Methods:

  • Formulation of a multi-objective mixed-integer linear programming problem for distribution center location.
  • Development of a carbon emission equivalent cost model, including dynamic transportation and static facility emissions.
  • Introduction of a customer satisfaction penalty cost model incorporating time window constraints.
  • Application of the Non-dominated Sorting Genetic Algorithm II (NSGA-II) with double-layer composite coding for optimization.

Main Results:

  • The study successfully established a model to evaluate the trade-offs between carbon emissions, customer satisfaction, and costs in cold chain logistics.
  • The proposed NSGA-II algorithm demonstrated efficiency in generating appropriate Pareto solutions for the multi-objective optimization problem.
  • Numerical results validated the algorithm's capability to handle the complexities of distribution center location decisions.

Conclusions:

  • Optimizing cold chain logistics distribution center location is vital for addressing environmental and customer satisfaction goals.
  • The developed model and NSGA-II algorithm offer a robust framework for decision-making in sustainable cold chain management.
  • This research provides valuable insights for improving the efficiency and environmental performance of cold chain operations.