Abstract: Systems and methods for accelerated online adaptive radiation therapy (“ART”) are described. The improvements to online ART are generally provided based on the use of textural analysis and machine learning algorithms implemented with a hardware processor and a memory. The described systems and methods enable more efficient and accurate online adaptive replanning (“OLAR”), which can also be implemented in clinically acceptable timeframes. For example, OLAR can be reduced from taking 10-30 minutes down to 5-10 minutes.

Abstract: Techniques for computing a feature based on variables may be provided. For example, historical realizations associated with a first variable may be accessed. The first variable may be associated with an item. Realizations of the first variable may be based on one or more factors associated with the item. Historical realization of a second variable associated with the item may also be accessed. The historical realizations of the first and second variables may be analyzed to generate an expected realization of the first variable as a function of the second variable. The feature may be computed based on the generated function.

Abstract: Various embodiments of a system and method for constraint-based reduction of a solution space for vehicle routing are described. Embodiments may include a system configured to identify sets of redundant routes within a solution space. For each given set of redundant routes, the system may utilize one or more constraints associated with conveying shipments on routes of the given set in order to eliminate one or more routes of that set from consideration. For each of multiple routes of the given set that have not been eliminated from consideration, the system may determine a respective cost associated with utilizing that route. The system may also, in response to determining that the cost associated with a particular route that has not been eliminated from consideration is less than the cost associated with other routes that have not been eliminated from consideration, add the particular route to a reduced solution space.

Abstract: Hybrid-heuristic optimization of competing portfolios of flight paths for flights through one or more sectors of an airspace represented by an air traffic system. In one embodiment, a hybrid-heuristic optimization process (100) includes one or more heuristic based processes (110), a genetic optimization process (120), an evaluation process involving an approximation model (130), an optimal portfolio selection process (140) and a validation process involving simulation (150) of the air traffic system.

Abstract: Hybrid-heuristic optimization of competing portfolios of flight paths for flights through one or more sectors of an airspace represented by an air traffic system. In one embodiment, a hybrid-heuristic optimization process (100) includes one or more heuristic based processes (110), a genetic optimization process (120), an evaluation process involving an approximation model (130), an optimal portfolio selection process (140) and a validation process involving simulation (150) of the air traffic system.