A multi-objective evolutionary algorithm for multi-period dynamic emergency resource scheduling problems. (March 2017)

• Record Type: Journal Article
• Authors: Zhou, Yawen; Liu, Jing; Zhang, Yutong; Gan, Xiaohui
• Is Part Of: Transportation research. Volume 99(2017)
• Page Start: 77
• Page End: 95
• Publication Date: 2017-03
• Subjects: Emergency resource scheduling problems -- Multi-period -- Multi-objective optimization -- Multi-objective evolutionary algorithm; Logistics -- Periodicals; Transportation -- Periodicals; 388.011
• DOI: 10.1016/j.tre.2016.12.011
• Languages: English
• ISSNs: 1366-5545

Abstract

Highlights: 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. 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).