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This paper presents a centralized scheduler that satisfies user requests for Position, Navigation, and Time (PNT) services from an ad-hoc, non-dedicated orbital constellation around the Moon. Traditional, dedicated GNSS networks provide service 24/7, which allows users to acquire localization services at-will. For ad-hoc networks, a coordinated schedule is needed to ensure Quality of Service (QoS) guarantees for user localization, while satisfying non-dedicated assets’ usage constraints. This scheduler bridges this coordination gap by leveraging Mixed Integer-Linear Programming (MILP) to schedule this “as-needed” localization service while respecting the constraints on each asset. In upcoming decades there is expected to be a substantial increase in Lunar missions. Many of these missions will feature low-cost surface assets near the moon’s polar regions and small-sat science missions in orbit. Most missions need PNT capabilities to ensure safe operations and meet their science objectives, but low-cost missions may not be able to support the large power, mass, and weight that a weak GNSS or DSN based navigation solution would entail. Asset localization has been demonstrated using a decentralized extended Kalman Filter (DEKF) in the previously presented Lunar Autonomous PNT System (LAPS). Within the LAPS simulation environment, a module has been developed to generate the coordinated user-asset schedules described above; this Service Scheduler Module (SSM) allows for complete end-to-end testing of the entire system. Within SSM, a user service request consists of a location on the Lunar surface, a cumulative service duration, and a window in which service must occur. SSM takes as input these requests and the LAPS-predicted positional degree of precision as the QoS for each available set of orbital assets. A simple, baseline MILP model is formulated to provide the highest-precision service balanced across all requests. To reflect the non-dedicated nature of the constellation, this baseline model is augmented with additional asset-specific load capacity constraints or availability constraints. The load capacity constraints limit total time spent providing service, and the availability constraints reflect blockout times or availability windows when the assets are not otherwise occupied. SSM outputs two schedules: the user schedule to indicate their service times and expected QoS, and a satellite schedule to be transmitted to the orbiting constellation, describing when each non-dedicated asset provides PNT service. SSM is predominantly implemented in MATLAB and allows the use of any MILP solver to generate the resulting schedules. This paper describes the SSM - LAPS interface, how the output of LAPS is used to construct the MILP, and how SSM provides user localization service while satisfying constraints. It will also demonstrate the tool’s flexibility for formulating schedules for the end user and the constellation, focusing on scenarios that match real-world proposed missions. It will detail how SSM can be used to compare the addition of load capacity constraints, satellite availability constraints, and QoS guarantees for the users. Finally, we describe how SSM can be used to support the design of the ad-hoc constellation itself. The resulting integrated capability will support the design of future ad-hoc Lunar PNT networks, enabling high-quality, low-cost Lunar exploration