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Algorithms for parallel machine scheduling: a case study of the tracking and data relay satellite system

Author

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  • S Rojanasoonthon

    (Graduate Program in Operations Research, University of Texas)

  • J F Bard

    (Graduate Program in Operations Research, University of Texas)

  • S D Reddy

    (Computer Sciences Corporation, New Carrollton)

Abstract

This paper presents two algorithms for scheduling a set of jobs with multiple priorities on non-homogeneous, parallel machines. The application of interest involves the tracking and data relay satellite system run by the US National Aeronautics and Space Administration. This system acts as a relay platform for Earth-orbiting vehicles that wish to communicate periodically with ground stations. The problem is introduced and then compared to other more common scheduling and routing problems. Next, a mixed-integer linear programming formulation is given but was found to be too difficult to solve for instances of realistic size. This led to the development of a dynamic programming-like heuristic and a greedy randomized adaptive search procedure. Each is described in some detail and then compared using data from a typical busy day scenario.

Suggested Citation

  • S Rojanasoonthon & J F Bard & S D Reddy, 2003. "Algorithms for parallel machine scheduling: a case study of the tracking and data relay satellite system," Journal of the Operational Research Society, Palgrave Macmillan;The OR Society, vol. 54(8), pages 806-821, August.
    • Handle: RePEc:pal:jorsoc:v:54:y:2003:i:8:d:10.1057_palgrave.jors.2601575
    DOI: 10.1057/palgrave.jors.2601575
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    References listed on IDEAS

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    Cited by:

    1. Jonathan F. Bard & Siwate Rojanasoonthon, 2006. "A branch‐and‐price algorithm for parallel machine scheduling with time windows and job priorities," Naval Research Logistics (NRL), John Wiley & Sons, vol. 53(1), pages 24-44, February.
    2. Siwate Rojanasoonthon & Jonathan Bard, 2005. "A GRASP for Parallel Machine Scheduling with Time Windows," INFORMS Journal on Computing, INFORMS, vol. 17(1), pages 32-51, February.
    3. J N D Gupta & A J Ruiz-torres & S Webster, 2003. "Minimizing maximum tardiness and number of tardy jobs on parallel machines subject to minimum flow-time," Journal of the Operational Research Society, Palgrave Macmillan;The OR Society, vol. 54(12), pages 1263-1274, December.
    4. Elena Nechita & Gloria Cerasela Crişan & Laszlo Barna Iantovics & Yitong Huang, 2020. "On the Resilience of Ant Algorithms. Experiment with Adapted MMAS on TSP," Mathematics, MDPI, vol. 8(5), pages 1-20, May.

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