Abstract: The present disclosure includes systems and methods for route planning. As an example, a computer implemented method for route planning can include generating a first portion of a planned route between a first location and a second location by assembling a set of previously traversed route segments each corresponding to one or more of a number of previously traversed routes, aggregating the set of previously traversed route segments with a number of route segments determined by a model-based route planning subsystem and corresponding to a second portion of the planned route, and causing the planned route to be provided to a display of a computing device.

Abstract: The present disclosure includes methods, devices, and systems for inferring system-level properties. One or more embodiments include generating a constraint model based on a system model having a number of components at different levels of abstraction and on a number of verified component properties. The constraint model can include a number of mission constraints modeling one or more mission requirements, a number of system constraints modeling one or more system-level properties, mid a number of component constraints modeling one or more component properties. One or more embodiments can include analyzing the constraint model with a constraint solver to determine whether one or more particular system-level properties can be inferred from the constraint model.

Abstract: The present disclosure includes methods, devices, and systems for inferring system-level properties. One or more embodiments include generating a constraint model based on a system model having a number of components at different levels of abstraction and on a number of verified component properties. The constraint model can include a number of mission constraints modeling one or more mission requirements, a number of system constraints modeling one or more system-level properties, mid a number of component constraints modeling one Or more component properties. One or more embodiments can include analyzing the constraint model with a constraint solver to determine whether one or more particular system-level properties can be inferred from the constraint model.

Abstract: A scheduler for a finite capacity process provides a schedule based on an integrated assessment of both discrete and continuous constraints. Given a list of products to be provided, the scheduler generates a set of activities required to produce the products and identifies resources required and the discrete and continuous constraints related to such resources. Activities are resized, and timelines are established for the activities as a function of deadlines for the product delivery for which the activities are related. Resource balancing heuristics are used to redistribute resource utilization to prevent bottlenecks. Data structures are used to keep track of constraints. Both discrete and continuous constraints are defined. Separate solver engines for the discrete and continuous constraint problems modify the constraints. The data structures are used to share and propagate constraints between the two engines.