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A Novel Hybrid Algorithm for Multiobjective Location-Allocation Problem in Emergency Logistics.

Hongrui Chu1, Yahong Chen2

  • 1School of Management and Engineering, Capital University of Economics and Business, Beijing 100070, China.

Computational Intelligence and Neuroscience
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Summary
This summary is machine-generated.

This study introduces an optimized emergency logistics system for effective post-disaster resource distribution. It minimizes deprivation, unsatisfied demand, and logistics costs, improving aid delivery to victims.

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Area of Science:

  • Operations Research
  • Disaster Management
  • Supply Chain Optimization

Background:

  • Increasing disaster frequency necessitates efficient post-disaster resource distribution.
  • Effective emergency logistics are crucial for minimizing victim suffering.

Purpose of the Study:

  • To establish an effective emergency logistics system for post-disaster scenarios.
  • To develop a multiobjective optimization model for a three-level logistics network.

Main Methods:

  • A multiobjective optimization model considering location and allocation decisions.
  • Incorporation of deprivation costs, unsatisfied demand costs, and logistics costs.
  • Development of a hybrid Firefly Algorithm-Genetic Algorithm (IFA-GA) for solving the model.

Main Results:

  • The proposed model effectively optimizes relief distribution networks.
  • The IFA-GA algorithm demonstrates validity and efficiency in solving the complex optimization problem.
  • Numerical results offer practical insights into post-disaster relief logistics.

Conclusions:

  • The study provides a robust framework for enhancing emergency logistics systems.
  • Optimized resource distribution significantly reduces suffering and improves aid delivery.
  • The developed IFA-GA algorithm is a powerful tool for complex disaster logistics optimization.