  In the aftermath of a hurricane, humanitarian logistics plays a critical role
in delivering relief items to the affected areas in a timely fashion. This
paper proposes a novel stochastic lookahead framework that implements a
two-stage stochastic programming model in a rolling horizon fashion to address
the evolving uncertain logistics system state during the post-hurricane
humanitarian logistics operations. The two-stage stochastic programming model
that executes in this rolling horizon framework is formulated as a
mixed-integer programming problem. The model aims to minimize the sum of
transportation and social costs. The social cost is measured as a function of
deprivation for unsatisfied demand. Our extensive numerical experiment results
and sensitivity analysis demonstrate the effectiveness of the proposed approach
in reducing the total cost incurred during the post-hurricane relief logistics
operations compared to the two-stage stochastic programming model implemented
in a static approach.
