Multi-period dynamic multi-objective emergency material distribution model under uncertain demand. (January 2023)

• Record Type: Journal Article
• Authors: Wan, Mengran; Ye, Chunming; Peng, Dajiang
• Is Part Of: Engineering applications of artificial intelligence. Volume 117:Part A(2023)
• Publication Date: 2023-01
• Subjects: Emergency material distribution -- Multi-period dynamic -- Uncertain demand -- Hybrid multi-objective salp swarm algorithm and sine cosine algorithm; Engineering -- Data processing -- Periodicals; Artificial intelligence -- Periodicals; Expert systems (Computer science) -- Periodicals; Ingénierie -- Informatique -- Périodiques; Intelligence artificielle -- Périodiques; Systèmes experts (Informatique) -- Périodiques; Artificial intelligence; Engineering -- Data processing; Expert systems (Computer science); Periodicals; 620.00285
• DOI: 10.1016/j.engappai.2022.105530
• Languages: English
• ISSNs: 0952-1976

Abstract

Abstract: This paper proposes a multi-period dynamic emergency material distribution (EMD) model under uncertain demand by considering the disaster degree and demand of different affected areas to improve the reasonability of disaster relief material distribution in post-disaster emergencies. The objective is to minimize the unsatisfied demand, materials distribution cost, and the risk of choosing the path to distribute materials. The model also focuses on the heterogeneity of emergency materials, the dynamics of demand, and the diversity of transportation tools. In addition, the demands and transportation times are described by fuzzy numbers to better fit with the real situation. To solve the problem we propose a hybrid multi-objective salp swarm algorithm and sine cosine algorithm (HMSSA-SCA). Furthermore, numerical examples of different scenarios and scales are solved and compared with the multi-objective salp swarm algorithm (MSSA), multi-objective evolutionary decomposition algorithm for emergency resource scheduling (MOEA/D-mdERS), non-dominated sorting genetic algorithm II (NSGA-II), and strength pareto evolutionary algorithm 2 (SPEA2) to verify the performance of the HMSSA-SCA algorithm. Finally, the floods and landslides disaster event in 2011 in Rio de Janeiro state, Brazil is used to verify the effectiveness and accuracy of the model and algorithm in the real case. Highlights: A multi-period dynamic emergency material distribution (EMD) model is proposed. An improved multi-objective salp swarm algorithm (HMSSA-SCA) is presented. Several new mechanisms are designed to propose HMSSA-SCA. Numeric experiments are carried out to validate the effectiveness of HMSSA-SCA.