Lockheed Martin Corporation

Pratik Jha

John Michael Lizzi

Rajesh Venkat Subbu

Alexander Suchkov

Jingqiao Zhang

Ian Crook

Jessica Chang

Abderrazak Tibichte

An airspace complexity reducing system is provided. The airspace complexity reducing system has a data storage device including data describing a multivariable model of an airspace complexity, the airspace complexity being a cumulative effect of factors that influence a system user's ability to manage aircraft in an associated airspace. The airspace complexity reducing system also has a selecting module configured to select a variable from a plurality of variables of the multivariable model and determine an amount by which to modify the selected variable to achieve a predetermined airspace complexity value. In addition, the airspace complexity reducing system has a suggestion module configured to determine a modification to the airspace that results in the determined variable modification and transmit the determined course of action to the system user.

Air traffic complexity reduction system utilizing multivariable models

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 () includes one or more heuristic based processes (), a genetic optimization process (), an evaluation process involving an approximation model (), an optimal portfolio selection process () and a validation process involving simulation () of the air traffic system.

Hybrid heuristic national airspace flight path optimization

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Herndon, VA, United States of America

Pratik Jha