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The HSABA for Emergency Location-Routing Problem

Author

Listed:
  • Siliang Luan
  • Qingfang Yang
  • Huxing Zhou
  • Zhongtai Jiang
  • Wei Wang
  • Zhuorui Wang
  • Ruijuan Chu

Abstract

This article presents a Location-Routing Problem (LRP) model to assist decision makers in emergency logistics. The model attempts to consider the relationship between the location of warehouses and the delivery routes in order to maximize the rescue efficiency. The objective function of the minimization of time and cost is established in the single-stage LRP model considering different scenarios. The hybrid self-adaptive bat algorithm (HSABA) is an improved nature-inspired algorithm for solving this LRP model, hard optimization problem. The HSABA with self-adaptation mechanism and hybridization mechanism effectively improves the defect of the original BA, that is, trapping into the local optima easily. An example is provided to prove the effectiveness of our model. The studied example shows that the single-stage LRP model can effectively select supply locations and plan rescue routes faced with different disasters and the HSABA outperforms the basic BA.

Suggested Citation

  • Siliang Luan & Qingfang Yang & Huxing Zhou & Zhongtai Jiang & Wei Wang & Zhuorui Wang & Ruijuan Chu, 2019. "The HSABA for Emergency Location-Routing Problem," Mathematical Problems in Engineering, Hindawi, vol. 2019, pages 1-12, July.
    • Handle: RePEc:hin:jnlmpe:5391687
    DOI: 10.1155/2019/5391687
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    Cited by:

    1. Md Ashikur Rahman & Rajalingam Sokkalingam & Mahmod Othman & Kallol Biswas & Lazim Abdullah & Evizal Abdul Kadir, 2021. "Nature-Inspired Metaheuristic Techniques for Combinatorial Optimization Problems: Overview and Recent Advances," Mathematics, MDPI, vol. 9(20), pages 1-32, October.

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