Abstract: A method of space travel using a high acceleration thrust vehicle in combination with a plurality of low acceleration thrust vehicles. A primary spacecraft has a kinetic launcher that is utilized to discharge a plurality of subsidiary spacecraft in order to navigate the primary spacecraft along a flight path. Each of the plurality of subsidiary spacecraft has a propulsion system, allowing each of the plurality of subsidiary spacecraft to navigate to a refueling point. The refueling point for each of the plurality of subsidiary spacecraft may be a central location or a unique position along a subsequent flight path. Each of the plurality of subsequent spacecraft is then reloaded onto the primary spacecraft or loaded onto a subsequent spacecraft for another voyage. The kinetic launcher can be repositioned in order to control the direction of the acceleration experienced by the primary spacecraft.

Abstract: A method of space travel using a high acceleration thrust vehicle in combination with a plurality of low acceleration thrust vehicles. A primary spacecraft has a kinetic launcher that is utilized to discharge a plurality of subsidiary spacecraft in order to navigate the primary spacecraft along a flight path. Each of the plurality of subsidiary spacecraft has a propulsion system, allowing each of the plurality of subsidiary spacecraft to navigate to a refueling point. The refueling point for each of the plurality of subsidiary spacecraft may be a central location or a unique position along a subsequent flight path. Each of the plurality of subsequent spacecraft is then reloaded onto the primary spacecraft or loaded onto a subsequent spacecraft for another voyage. The kinetic launcher can be repositioned in order to control the direction of the acceleration experienced by the primary spacecraft.

Abstract: A method and system for solving an optimization problem comprising a plurality of dynamic constraints. A genetic algorithm is used to iteratively generate potential solutions to the problem. A constraint graph is used to model the plurality of dynamic constraints, and any potential solution that does not correspond to a connected subgraph of the constraint graph is infeasible and discarded. Real-time changes in dynamic constraints are incorporated by modification of the constraint graph between iterations of the genetic algorithm. An exemplary embodiment comprising the scheduling of air missions is presented.

Abstract: A method and system for solving an optimization problem comprising a plurality of dynamic constraints. A genetic algorithm is used to iteratively generate potential solutions to the problem. A constraint graph is used to model the plurality of dynamic constraints, and any potential solution that does not correspond to a connected subgraph of the constraint graph is infeasible and discarded. Real-time changes in dynamic constraints are incorporated by modification of the constraint graph between iterations of the genetic algorithm. An exemplary embodiment comprising the scheduling of air missions is presented.

Abstract: This invention enables a bandwidth efficient computer simulation of sustained contact between objects. When an object comes into sustained contact with a second object, it will communicate to the second object a transfer function describing the contact, and vice-versa. The transfer function enables the objects to simulate the sustained contact for as long as the contact continues, eliminating any need for further network communication between the objects regarding the state of the contact until the contact terminates.