A multi-objective evolutionary algorithm for multi-period dynamic emergency resource scheduling problems
Yutong Zhang and
Transportation Research Part E: Logistics and Transportation Review, 2017, vol. 99, issue C, 77-95
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).
Keywords: Emergency resource scheduling problems; Multi-period; Multi-objective optimization; Multi-objective evolutionary algorithm (search for similar items in EconPapers)
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