Journal
TRANSPORTATION RESEARCH PART E-LOGISTICS AND TRANSPORTATION REVIEW
Volume 99, Issue -, Pages 77-95Publisher
PERGAMON-ELSEVIER SCIENCE LTD
DOI: 10.1016/j.tre.2016.12.011
Keywords
Emergency resource scheduling problems; Multi-period; Multi-objective optimization; Multi-objective evolutionary algorithm
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Funding
- National Natural Science Foundation of China (NSFC) [61271301]
- Outstanding Young Scholar Program of NSFC [61522311]
- Overseas, Hong Kong & Macao Scholars Collaborated Research Program of NSFC [61528205]
- Research Fund for the Doctoral Program of Higher Education of China [20130203110010]
- Fundamental Research Funds for the Central Universities [K5051202052]
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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). (C) 2017 Elsevier Ltd. All rights reserved.
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