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181 to 185 of 185 Results
ASPEN: A Framework for Automated Planning and Scheduling of Spacecraft Control and Operations
Jul 14, 1997
Yan, David; Fukunaga, Alex S.; Rabideau, Gregg; Chien, Steve, 1997, "ASPEN: A Framework for Automated Planning and Scheduling of Spacecraft Control and Operations", https://hdl.handle.net/2014/22263, Tokyo, JPL Open Repository
In this paper, we describe ASPEN (Automated Planning/Scheduling Environment), a modular, reconfigurable application framework which is capable of supporting a wide variety of planning and scheduling applications.
Towards an Application Framework for Automated Planning and Scheduling
Feb 2, 1997
Fukunaga, Alex; Rabideau, Greg; Chien, Steve; Yan, David, 1997, "Towards an Application Framework for Automated Planning and Scheduling", https://hdl.handle.net/2014/27637, Snowmass, CO, JPL Open Repository
A number of successful applications of automated planning and scheduling applications to spacecraft operations have recently been reported in the literature. However, these applications have been one-of-a-kind applications that required a substantial amount of development effort....
Automating the Process of Optimization in Spacecraft Design
Feb 1, 1997
Fukunaga, Alex; Chien, Steve; Mutz, Darren; Sherwood, Robert L.; Stechert, Andre D., 1997, "Automating the Process of Optimization in Spacecraft Design", https://hdl.handle.net/2014/27636, Aspen, CO, JPL Open Repository
Spacecraft design optimization is a difficult problem, due to the complexity of optimization cost surfaces, and human expertise in optimization that is necessary in order to achieve good results. In this paper, we propose the use of a set of generic, metaheuristic optimization al...
The Multimission VICAR Planner: A Fielded Planning System for Scientific Data Analysis
Oct 1, 1995
Chien, Steve, 1995, "The Multimission VICAR Planner: A Fielded Planning System for Scientific Data Analysis", https://hdl.handle.net/2014/32044, Assisi, Italy, JPL Open Repository
The Multimission VICAR Planner (MVP) system is an AI planning system which constructs
Learning Search Control Knowledge for Deep Space Network Scheduling
Jun 27, 1993
Gratch, Jonathan; Chien, Steve; DeJong, Gerald, 1993, "Learning Search Control Knowledge for Deep Space Network Scheduling", https://hdl.handle.net/2014/35258, Amherst, MA, USA, JPL Open Repository
While the general class of most scheduling problems is NP-hard in worst-case complexity, in practice, for specific distributions of problems and constraints, domain-specific solutions have been shown to perform in much better than exponential time.
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