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

•A multi-objective optimization model is designed for multi-period dynamic emergency resource scheduling (ERS) problems.•MOEA/D-mdERSis proposed to solve the designed modelbased on the properties of multi-period dynamic ERS problems.•The experimental results show that MOEA/D-mdERS can find a set of...

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Published in:Transportation research. Part E, Logistics and transportation review Vol. 99; pp. 77 - 95
Main Authors: Zhou, Yawen, Liu, Jing, Zhang, Yutong, Gan, Xiaohui
Format: Journal Article
Language:English
Published: Elsevier India Pvt Ltd 01.03.2017
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ISSN:1366-5545, 1878-5794
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Abstract •A multi-objective optimization model is designed for multi-period dynamic emergency resource scheduling (ERS) problems.•MOEA/D-mdERSis proposed to solve the designed modelbased on the properties of multi-period dynamic ERS problems.•The experimental results show that MOEA/D-mdERS can find a set of better candidate solutions than NSGA-II. 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).
AbstractList •A multi-objective optimization model is designed for multi-period dynamic emergency resource scheduling (ERS) problems.•MOEA/D-mdERSis proposed to solve the designed modelbased on the properties of multi-period dynamic ERS problems.•The experimental results show that MOEA/D-mdERS can find a set of better candidate solutions than NSGA-II. 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).
Author Zhou, Yawen
Liu, Jing
Zhang, Yutong
Gan, Xiaohui
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  givenname: Yutong
  surname: Zhang
  fullname: Zhang, Yutong
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  givenname: Xiaohui
  surname: Gan
  fullname: Gan, Xiaohui
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Multi-objective optimization
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Multi-objective evolutionary algorithm
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Snippet •A multi-objective optimization model is designed for multi-period dynamic emergency resource scheduling (ERS) problems.•MOEA/D-mdERSis proposed to solve the...
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SubjectTerms Emergency resource scheduling problems
Multi-objective evolutionary algorithm
Multi-objective optimization
Multi-period
Title A multi-objective evolutionary algorithm for multi-period dynamic emergency resource scheduling problems
URI https://dx.doi.org/10.1016/j.tre.2016.12.011
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