When there is a need to move cargo across the world in the fastest possible manner, airlift is the prime solution. Due to the potential extreme requirements of airlift, aircraft have to be capable of performing in a myriad of operational environments. To support future aircraft d
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When there is a need to move cargo across the world in the fastest possible manner, airlift is the prime solution. Due to the potential extreme requirements of airlift, aircraft have to be capable of performing in a myriad of operational environments. To support future aircraft design loops, this work proposes a framework which couples aircraft design and operational effectiveness in an agent-based simulation, allowing a more direct evaluation of design choices. Aircraft are modelled with inputs akin to typical design tool outputs, and airlift operational objectives and events are parameterized to allow for user customization and mission tailoring. To deal with stochastic and unexpected events that occur within airlifts, such as aircraft servicing, cargo demand reformulation and airbase access restriction, the aircraft and cargo are modelled as agents and managed by a dispatcher. Aircraft bid for cargo with flights which are configured by the dispatcher, allowing cargo to choose its flight path according to the airlift objective. Through analyzing a theoretical disaster relief mission, the impact of disruptive events on airlift time, cost and cargo throughput is shown to be significant, motivating their inclusion in future analysis. An exploration of aircraft design and airlift objectives is also analyzed, which highlighted the variance in airlift performance due to changes in aircraft payload-range and operational logics. The results demonstrate the framework's ability to capture the varying complexities of the airlift system, exemplifying its utility in future airlift and aircraft design optimization and resilience testing.