Optimisation approaches for planning and operation of relief efforts during flood
Creators: name: Insani, Nur
Publisher: name: RMIT University
Year: 2024
Subjects: classificationCode: 490108
subject: Operations research
classificationCode: 490304
subject: Optimisation

description: The frequency and intensity of all types of natural disasters - floods, landslides, hurricanes, earthquakes, storms or droughts - have increased from around 50 events a year during the 1970s to 401 events in 2021, and these floods contribute most to the number of deaths and the total of those affected. Beyond human losses and all the damage caused by a natural disaster, there is also an evident need for shelter and emergency relief to be provided for the victims in a time-critical manner.

A disaster relief operation (DRO) includes the evacuation of people from disaster-stricken areas to safer places, and planning, implementing and controlling the efficient, cost-effective flow of goods to alleviate the suffering of vulnerable people. It plays an essential role in saving lives. The operation involves tasks such as the search and rescue of affected people through evacuation, locating and establishing emergency facilities, distributing relief commodities and providing health and medical assistance. Many approaches for modelling disaster relief operations have been proposed over the decades, and most of them focus on minimising the travelling times or costs after a disaster strikes. However, evacuating and transferring everyone at risk to the required locations with sufficient vehicles before a disaster strikes is pivotal to avoiding more significant losses. Yet current vehicle routing problem (VRP) models mostly concentrate only on one single routing decision. Furthermore, the existing models are commonly applied only in the post-disaster stage, where the water has already hit the prone areas. 

Four key optimisation models and a metaheuristic approach have been developed to address the problem of vehicle assignment and its routing decision for evacuation and relief distribution in the most efficient way. The effectiveness of each model is defined in terms of its ability to calculate the minimum number of vehicles required to do the tasks for each given problem. 

Owing to evacuation's importance at a crucial time, this study develops a new short-notice flood evacuation model by utilising public transportation to evacuate a number of people, particularly in areas with a high population. The model has been constructed as a complex system consisting of various components such as multiple evacuation points and temporary shelters, and differing numbers of evacuees. A set of homogeneous vehicles is utilised to carry out the operation, and the aim is to finish the task before the water reaches the predicted areas. The developed model aims to optimise the number of vehicles required and the sequence of trips in order to save all evacuees. Because there may be limitations in the availability of vehicles in the early stages of a flood, the model integrates some VRP extension strategies: splitting the demand (i.e. split delivery), and reusing vehicles (i.e. multi-trips). This integration will allow more flexibility for the vehicles to cover all the necessary routes within a given time horizon. The computed solutions demonstrate that the developed model is able to generate an evacuation plan to transfer all evacuees with fewer vehicles than the standard vehicle routing model. This work is significant as it helps authorities to identify more effectively the number of vehicles that are actually needed.

Several new approaches were then utilised in the next phase of the project to tackle some real-world uncertainties, such as the flow of the floodwaters and the number of evacuees. In this phase, the previously proposed model was extended through an opening time window constraint by considering the propagation of the flood over time. Another key feature of the model is consideration of the time required to load the evacuees at each evacuation point (EP) and to unload them at each shelter. The model is formulated as a split delivery multi-trip vehicle routing problem with a time window. To capture the uncertain aspects of the demands, Poisson distribution and uniform distribution were used as tools to generate different numbers of evacuees and closing time windows at each EP. The effectiveness of the developed models was then assessed by applying them to self-generated flood problems or synthetic instances of various sizes, and to the real-life case of the 2019 flood in Indonesia.

Further, this study has also developed another innovative relief operation model that integrates the two highest priority tasks in the early stages of a flood: evacuation and relief distribution. The integration of these two tasks within one model allows us to efficiently identify the need for vehicles to evacuate people and distribute the relief simultaneously. A set of homogeneous vehicles can be assigned to evacuate victims and another set of vehicles to deliver emergency relief from the distribution centres. This model also takes into consideration the capacities of various resources, including vehicles, shelters and distribution centres. The effectiveness of the developed model is discussed in contrast to the hierarchical model. It is concluded that the integration of some tasks into one complete system optimises the number of vehicles required more effectively.

As it is in the nature of all routing problems that it is difficult to solve a VRP of realistic size within a reasonable time, the last part of the research was dedicated to efforts toward solving a realistic-sized VRP using a metaheuristic approach called the modified genetic algorithm (MGA). We then utilised the MGA to solve the developed routing models for both synthetic and real-world instances. The results of the experimental evaluations confirm that the solution approach can provide the best solutions for evacuation as well as integrated models within a reasonable time and has the potential to provide real-time decision supports for related authorities.

In conclusion, the models developed in this study reveal the importance and contribution of mathematical approaches in disaster management, particularly for planning the operational tasks in evacuation and relief distribution.