Bi-objective robust optimisation on relief collaborative distribution considering secondary disasters

Developing an effective emergency collaborative distribution system is critical to improve on-time response performance, especially considering secondary disasters. To address the challenge, this paper investigates a bi-objective robust optimisation model on relief collaborative distribution among three echelons of authorities, the province, the municipality, and the county, which aims to minimise the total travel time and the total humanitarian logistics cost simultaneously. The optimal location of relief supply facilities and the relief distribution schemes will be determined by the optimisation model, which considers uncertain demand and travel time. Moreover, two robust optimisation methods are utilised to deduce the robust counterparts of the proposed model. An epsilon-constraint-based approach is used to solve the bi-objective optimisation model. A real-world case study based on an earthquake and aftershocks with different magnitudes in Yunnan Province is provided. The results show that incorporating secondary disaster scenarios contributes to reducing the total travel time and cost. For making full use of emergency resources and preventing situations from worsening, the centralised decision scheme is more effective than the decentralised one. The uncertainty of demand of primary disaster relief has a higher impact on the optimal solution than that of travel time.

Automated summary

This paper investigates a bi-objective robust optimization model on relief collaborative distribution among three echelons of authorities to address the challenge of developing an effective emergency collaborative distribution system. The optimal location of relief supply facilities and the relief distribution schemes are determined by the model, which considers uncertain demand and travel time. The results show that incorporating secondary disaster scenarios reduces total travel time and cost, and the centralised decision scheme is more effective in utilizing emergency resources and preventing situations from worsening.