<![CDATA[Recurrent flooding in Aceh, North Sumatra, and West Sumatra reflects the increasingly complex challenges of providing public services in emergency situations. In large-scale floods, service disruptions are triggered not only by the increasing number of victims and the need for assistance, but also by disruptions to the operational capacity of public service facilities, such as hospitals, police, fire departments, and transportation access. These disruptions result in slow responses and low resource utilization efficiency, ultimately increasing the risk of loss of life. This research aims to formulate a mathematical optimization model for emergency public services during floods, taking into account resource limitations and the simultaneous reduction in the capacity of service centers. The model was developed to minimize response times and delays in victim handling, while also providing a conceptual contribution to the development of public service optimization studies and strengthening healthcare resilience within a Smart City framework. The research approach used is fundamental research through linear programming-based mathematical modeling. The emergency public service problem is formulated as a multi-agency optimization model that includes an objective function and various constraints, such as service capacity, victim priorities, resource limitations, and access barriers due to flooding. The analysis is conducted through conceptual simulations on various service capacity reduction scenarios to examine the solution characteristics and theoretical model consistency.]]>
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