Multi-Objective Scheduling for Space Science Missions
Mark D. Johnston* and Mark E. Giuliano**
*Jet Propulsion Laboratory, California Institute of Technology, 4800 Oak Grove Drive, Pasadena, CA 91109, USA
**Space Telescope Science Institute, 3700 San Martin Drive, Baltimore, MD 21219, USA
-  K. Deb, “Multi-Objective Optimization Using Evolutionary Algorithms,” New York: John Wiley & Sons, 2001.
-  A. Abraham, L. Jain, and R. Goldberg, “Evolutionary Multiobjective Optimization,” Berlin: Springer, 2005.
-  Y. Collette and P. Siarry, “Multiobjective Optimization,” Berlin: Springer, 2003.
-  S. Kukkonen and J. Lampinen, “GDE3: The Third Evolution Step of Generalized Differential Evolution,” in The 2005 Congress on Evolutionary Computation, 2005.
-  S. Kukkonen, and J. Lampinen, “Performance assessment of generalized differential evolution 3 with a given set of constrained multi-objective test problems,” in Proc. of the Eleventh conference on Congress on Evolutionary Computation, Trondheim, Norway, 2009.
-  M. D. Johnston, “Multi-Objective Scheduling for NASA’s Deep Space Network Array,” in Int. Workshop on Planning and Scheduling for Space (IWPSS-06), Baltimore, MD: Space Telescope Science Institute, 2006.
-  M. D. Johnston, “An Evolutionary Algorithm Approach to Multi-Objective Scheduling of Space Network Communications,” Int. J. of Intelligent Automation and Soft Computing, Vol.14, pp. 367-376, 2008.
-  K. Price, R. Storn, and J. Lampinen, “Differential Evolution: A Practical Approach to Global Optimization,” Berlin: Springer, 2005.
-  R. Storn and K. Price, “Differential Evolution – a simple and efficient heuristic for global optimization over continuous spaces,” J. of Global Optimization, Vol.11, pp. 341-350, 1997.
-  K. Deb, A. Pratap, S. Agarwal, and T. Meyarivan, “A fast and elitist multiobjective genetic algorithm: NSGA-II,” IEEE trans. on evolutionary computation, Vol.6, No.2, pp. 182-197, 2002.
-  S. Kukkonen and K. Deb, “Improved Pruning of Non-Dominated Solutions Based on Crowding Distance for Bi-Objective Optimization Problems,” Proc. of the 2006 Congress on Evolutionary Computation (CEC 2006), 2006.
-  R. Spence, “Information Visualization,” ACM Press, Addison-Wesley, 2001.
-  J. Tidwell, “Designing Interfaces,” O’Reilly, 2005.
-  M. E. Giuliano and M. D. Johnston, “Visualization Tools For Multi-Objective Algorithms. Demonstration,” in Int. Conf. on Automated Planning and Scheduling, Toronto, Canada, 2010.
-  M. Giuliano and M. D. Johnston, “Developer Tools for Evaluating Multi-Objective Algorithms,” in 6th Int.Workshop on Planning and Scheduling in Space (IWPSS), Darmstadt, Germany, 2011.
-  R. Rager and M. Giuliano, “Evaluating Scheduling Strategies for JWST Momentum Management,” in 5th Int.Workshop on Planning and Scheduling for Space, pp. 235-243, 2006.
-  M. D. Johnston and G. E. Miller, “Spike: Intelligent Scheduling of Hubble Space Telescope Observations,” in Intelligent Scheduling, M. Zweben and M. Fox (Eds.), Morgan Kaufmann: San Mateo, pp. 391-422, 1994.
-  M. Giuliano, R. Rager, and N. Ferdous, “Towards a Heuristic for Scheduling the James Webb Space Telescope,” in ICAPS, Providence, RI., pp. 160-167, 2007.
-  M. Giuliano and M. D. Johnston, “Multi-Objective Evolutionary Algorithms for Scheduling the James Webb Space Telescope,” in Int. Conf. on Automated Planning and Scheduling (ICAPS), Sydney, Australia, 2008.
-  B. G. Paczkowski and T. L. Ray, “Cassini Science Planning Process,” in SpaceOps, 2004.
-  B. G. Paczkowski, B. Larsen, and T. L. Ray, “Managing Complexity to Maximize Science Return: Science Planning Lessons Learned from Cassini,” in Aerospace Conf., Big Sky, MT., pp. 1-14, 2009.
-  ESA. Cluster II Mission.
Available from: http://sci.esa.int/science-e/www/area/index.cfm?fareaid=8.
-  Cluster II Wideband Data plasma wave investigation.
Available from: http://www-pw.physics.uiowa.edu/plasma-wave/istp/cluster/.
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