Relief supply collaboration for emergency logistics responses to large-scale disasters

Abstract

This paper proposes a novel relief supply collaboration approach to address the issue of post-disaster relief supply–demand imbalance in emergency logistics (EL) operations. This proposed approach involves two levels of recursive functions: (1) a two-stage relief supplier clustering mechanism for time-varying multi-source relief supplier selection and (2) the use of stochastic dynamic programming model to determine a multi-source relief supply that minimises the impact of relief supply–demand imbalance during EL response. The distinctive features of this proposed approach are to identify the potential relief suppliers and to minimise the imbalanced supply–demand impact under relief supply collaboration. Scenario design and model tests are conducted to demonstrate that relief supply collaboration with grouped relief suppliers has a significant benefit of alleviating the impact of imbalanced relief supply–demand, relative to collaboration with ungrouped ones.

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