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Large Scale Energy Efficient Sensor Network Routing Using a Quantum Processor Unit
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A Hyperheuristic Approach for Location-Routing Problem of Cold Chain Logistics considering Fuel Consumption.

Zheng Wang1, Longlong Leng2, Shun Wang2

  • 1School of Computer Science and Technology, Zhejiang University of Technology, Hangzhou 310023, China.

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|May 15, 2020
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Summary
This summary is machine-generated.

This study optimizes cold chain logistics by balancing costs and delivery times. A new hyperheuristic framework improves efficiency and customer satisfaction while reducing carbon emissions.

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Area of Science:

  • Operations Research
  • Supply Chain Management
  • Environmental Science

Background:

  • Cold chain logistics face intense competition and pressure for low-carbon operations.
  • Balancing economic, social, and environmental factors is crucial for sustainable development.

Purpose of the Study:

  • To develop a biobjective mathematical model for cold chain logistics networks.
  • To optimize total cost and distribution period, considering various cost components and environmental impact.

Main Methods:

  • A multiobjective hyperheuristic optimization framework was proposed.
  • The framework incorporates novel selection strategies and acceptance criteria.
  • Performance was compared against the NSGA-II algorithm.

Main Results:

  • The proposed algorithm demonstrated superior performance compared to NSGA-II.
  • The model successfully optimized cold chain logistics networks.
  • A diverse Pareto solution set was generated for decision-making.

Conclusions:

  • The developed framework offers an effective approach for optimizing cold chain logistics.
  • Decision-makers can utilize the Pareto set for informed network selection.
  • The study contributes to more sustainable and efficient cold chain operations.