Queue Simulation for Flood Relief Distribution Following Disasters Using Parametric Regression Technique

Abstract

The distribution of post-flood disaster aid often faces obstacles such as long queues, extended
waiting times, and inefficient aid distribution. This condition can hinder the fulfilment of the
basic needs of the affected community, especially during the emergency response phase. This
research aims to analyse the queuing system in the process of distributing aid after a flood disaster
and to simulate a more effective service pattern using the parametric regression method. This
method is used to identify the influence of certain variables, such as the number of refugees, the
capacity of officers, and service time, on queue length and waiting time. Research data were
obtained from field observations, documentation, and interviews at the aid distribution locations.
The analysis results show that the increase in the number of aid recipients, not matched by service
capacity, has caused a significant increase in queues. The simulation conducted shows that
adjusting the number of officers and accelerating service time can reduce queue length and
improve the efficiency of aid distribution. Thus, the application of queue simulation based on
parametric regression can serve as an aid in planning a faster, more accurate, and organised aid
distribution system in post-flood disaster conditions.