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A multi-objective evolutionary algorithm for multi-period dynamic emergency resource scheduling problems

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  • Zhou, Yawen
  • Liu, Jing
  • Zhang, Yutong
  • Gan, Xiaohui

Abstract

The resource distribution in post-disaster is an important part of emergency resource scheduling. In this paper, we first design a multi-objective optimization model for multi-period dynamic emergency resource scheduling (ERS) problems. Then, using the framework of multi-objective evolutionary algorithm based on decomposition (MOEA/D), an MOEA is proposed to solve this model. In the proposed algorithm, new evolutionary operators are designed with the intrinsic properties of multi-period dynamic ERS problems in mind. The experimental results show that the proposed algorithm can get a set of better candidate solutions than the non-dominated sorting genetic algorithm II (NSGA-II).

Suggested Citation

  • Zhou, Yawen & Liu, Jing & Zhang, Yutong & Gan, Xiaohui, 2017. "A multi-objective evolutionary algorithm for multi-period dynamic emergency resource scheduling problems," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 99(C), pages 77-95.
    • Handle: RePEc:eee:transe:v:99:y:2017:i:c:p:77-95
    DOI: 10.1016/j.tre.2016.12.011
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