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Robust dual sourcing inventory routing optimization for disaster relief.

Weibo Zheng1,2, Hong Zhou1,2

  • 1School of Economics and Management, Beihang University, Beijing, China.

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Summary

This study addresses disaster relief logistics by optimizing replenishment strategies. It introduces a dual sourcing policy and a robust optimization model for efficient inventory routing, improving disaster response capabilities.

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Area of Science:

  • Operations Research
  • Logistics Management
  • Disaster Management

Background:

  • Disaster relief operations require efficient replenishment of supplies to multiple shelters.
  • Existing inventory routing problems often do not account for variable lead times or dual sourcing.

Purpose of the Study:

  • To develop a robust optimization model for inventory routing in disaster relief.
  • To incorporate dual sourcing and dynamic lead times into replenishment decisions.
  • To create an efficient algorithm for solving the proposed model.

Main Methods:

  • Formulated a robust optimization model for the inventory routing problem.
  • Decomposed the problem into a routing master-problem and inventory sub-problems.
  • Derived a closed-form solution for inventory sub-problems.
  • Developed an adaptive large neighborhood search (ALNS) algorithm.

Main Results:

  • The proposed robust optimization model effectively determines optimal replenishment quantities, modes, and routes.
  • The ALNS algorithm demonstrates feasibility and efficiency in solving the complex inventory routing problem.
  • Numerical experiments validate the algorithm's performance on benchmark test suites.

Conclusions:

  • The study provides a novel approach to inventory routing for disaster relief with dual sourcing.
  • The developed robust optimization model and ALNS algorithm offer practical solutions for enhancing disaster response logistics.
  • The findings contribute to more resilient and efficient supply chain management in crisis situations.