With 700+ participants and 50+ speakers from around the world, we are thrilled to say that this year's online event was a success! Better still, all sessions are now available to watch on YouTube.
This stream has a particular focus on the management of humanitarian disasters.
Common OR techniques such as modelling and optimisation are particularly invaluable when it comes to forecasting emergency service demand, optimising warehouse locations for emergency supplies or optimising disaster preparedness and disaster responses.
Anyone with an interest in disaster management or sustainable development will find this stream especially interesting and educational.
In this talk, we will present the latest development of Relief-OpS, a project funded by the EPSRC (UK). The overall objective of this project is to develop an optimisation-via-simulation (OvS) method to solve a multi-objective Integrated Stochastic Disaster Risk Management (ISDRM) problem. The method will find optimal warehouse locations and replenishment policies for perishable relief items needed following a natural disaster, subject to practical and operational constraints. It will also find optimum routing for relief distribution when a disaster strikes.
We will consider multi-disaster scenarios, practical constraints and multi-criteria objective functions that are relevant to the relief supply chains in West Java province in Indonesia. West Java province is chosen because it has the highest multi disaster risk in Indonesia due to the population size, population density, high contribution to Indonesian GDP and being the centre of rice (a staple food in Indonesia) production in Java island. While we will work closely with the model users from government units in West Java, research outcomes will be shared with model users from all provinces in Indonesia.
The project’s twitter handle is @OpSRelief (http://www.twitter.com/opsrelief).
This stream will feature three 20-minute talks. Meet the experts who will be delivering each of the sustainable development goals talks below.
University of Southampton
University of Southampton
Our research programme is working with the Indonesian emergency ambulance (118) service to help them forecast emergency demand and make critical decisions on the optimal types, capacities and geographical locations of vehicles. Such factors directly impact on the probability of patient survival, the ability to respond to major disasters, and the overall quality of care provided. However, there are many challenges faced in Indonesia including vast geographical areas, traffic, and inadequate numbers of ambulances.
Indonesia commonly experiences natural disasters and conflicts, which means that the ability to respond to major events is also limited and thus chances of survival are low. The Lombok and Palu earthquakes in 2018 alone are estimated to have killed 2,800; the Indian Ocean tsunami in 2004 killed over 170,000 Indonesians.
This talk will describe findings of the research project to date, including an analysis of survey data collected from Jakarta hospitals and progress on developing a spatiotemporal forecast of demand. We will also describe the approach to EMS allocations for a population with multiple medical needs, using a fleet consisting of multiple vehicle types with differing travel speeds. This will be achieved via the creation of an optimisation and simulation decision-support framework that will be deployed by 118.
Natural disasters have grave societal, economic, and environmental consequences. The optimisation of disaster preparedness and response decisions offers ample opportunities for reducing these devastating impacts. However, the available approaches are mostly based on general assumptions that tend to oversimplify the decision-making needs of disaster management agencies. This leads to inefficient allocation and use of scarce resources, which hinders the acceptability and implementation of the proposed solutions. The modelling, computational and data management challenges stemming from the complexity of the real-world decision-making environment need to be addressed to create more effective disaster responses.
The RESPOND-OR (EPSRC/GCRF funded) project aims to address this by developing models that better incorporate the requirements of emergency preparedness and response stakeholders. In this presentation, we provide an overview of the RESPOND-OR project, focusing on the methodological framework used to incorporate the real-world complexities and stakeholder requirements in the proposed emergency response and preparedness Decision Support System, and we report on our modelling findings.
University of Lancaster