Probabilistic allocation and scheduling of multiple resources for emergency operations; a Victorian bushfire case study

The optimization of scheduling and sequencing of multiple resources during disaster management is a challenge due to substantial uncertainty. This paper presents an emergency operation model that aims to facilitate the scheduling and sequencing resources using multiple stochastic scenarios. The proposed model integrates GIS and Mixed Integer Programming (MIP) approaches. The ultimate goal of this paper is to provide a solution framework to identify the most persistent best compromised plan with a specified confidence level. The scheduling of multiple resources under uncertainty (MRSU) model is applied to a case study using data from the Black Saturday bushfires in 7 February 2009 in Victoria, Australia. Several probabilistic scenarios are analyzed to determine the most frequent emergency operation plan. Several probabilistic scenarios are analyzed to determine the most persistent best compromised emergency operation plan. The results indicate that the model can generate plans to schedule multiple resources, thus providing effective service in most emergency scenarios.