A multi-objective evolutionary algorithm for multi-period dynamic emergency resource scheduling problems - Zhou, Yawen; Liu, Jing; Zhang, Yutong; Gan, Xiaohui (Transportation research. Part E, Logistics and transportation review, 2017)
•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).