Designing a resilient relief supply network for natural disasters in West Java Indonesia using optimisation-via-simulation: Relief-OpS In this project, we will develop methods that optimise the delivery of essential relief items following a natural disaster. These include optimising warehouse locations; inventory management strategies particularly for perishable relief items; and robust routing for post-disaster distribution. The optimisation will make use of an agent based simulation model that we will build with input from key decision-makers, designed to mimic the complexities of post-disaster relief efforts.  The Sendai Framework for Disaster Risk Reduction 2015-2030 puts a strong emphasis on Disaster Risk Management, acknowledging the importance of risk management and strengthening resilience against disasters. Based on the Sendai Framework, the Indonesian government produces a national plan for disaster risk management which highlights the needs for Indonesia to improve its preparedness and response to natural disasters. To execute the plan, Indonesia has established the national board for disaster management overseeing several regional boards for disaster management.  DRM activities span four phases: mitigation, preparedness, response, and recovery. Based on the Indonesian national plan, we focus our research on the preparedness phase (activities performed prior to disaster to allow more efficient response activities such as pre-positioning inventory of relief items) and the response phase (activities following a disaster to reduce its impact). The majority of research in DRM solves the preparedness and response phases of DRM separately, leading to suboptimal solutions. Furthermore, the solutions tend to be based on just one type of disaster. Another gap is that most research assumes that relief items are non-perishable, relief distribution is well coordinated, and demand and damages are known immediately after a disaster. Our focus on multi-disaster situations incorporating all of the complexities of multiple organisations providing relief support will result in more realistic models, filling the gaps in the literature in DRM and resulting in more impact. The research also extends previous Optimisation-via-Simulation methodology to multi-objective, multi-level problems.  In this project, we will work with West Java regional board from specifying the requirements for the decision support system to developing realistic scenarios to evaluate our methods. 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 production in Java island (rice is the main staple food in Indonesia). As we will implement the national standard procedures for disaster preparedness and response, the decision support system can be customised by other regional boards to suit the characteristics of their regions by changing the parameters (for example, map, demography, infrastructure). Therefore, we will also organise a practitioner workshop to present our findings and to provide training for all regional boards to use the decision support system. The decision support system can also be used for training purposes which will strengthen the preparedness of the regional board officials.  Finally, this project will build capacity in this vital area of research. The research assistants in the UK and Indonesia will gain from regular project meetings, interactions with investigators and the scientific advisory board members, and relevant training in Southampton, Padjadjaran or other places in the UK and South East Asia. We will also organise a research workshop for Indonesian researchers who are interested in OvS, ABS and Operational Research in DRM The Global Challenges Research Fund (GCRF) supports cutting-edge research to address challenges faced by developing countries. The fund addresses the UN sustainable development goals. It aims to maximise the impact of research and innovation to improve lives and opportunity in the developing world.