Multi-period dynamic multi-objective emergency material distribution model under uncertain demand

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.