Identifying optimal design requirements of new systems that operate along with existing systems to provide a set of overarching capabilities is challenging due to the tightly coupled effects that setting requirements on a system's design (here, military transportation aircraft) can have on how the system is being used (here, how the aircraft is allocated to carry cargo on specified routes). This research builds on prior work to further develop a quantitative approach that generates optimum design requirements of new, yet-to-be-designed systems that, when serving alongside other systems, will optimize fleet-level objectives while considering the effect of demand uncertainties in the service network and specific payload capacity requirements for the new system. The approach is demonstrated for two example problems resembling missions of the USAF Air Mobility Command cargo-carrying fleet. Solving the multi-objective formulation using the subspace decomposition framework provides a set of Pareto optimal solutions for different tradeoff opportunities between fleet-level cost and fleet-level productivity. The Pareto front enables the decision-maker to select a desired balance of fleet-level cost and fleet-level productivity, and identify the corresponding optimized design of the new system.
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