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Scheduling Coast Guard District Cutters

Author

Listed:
  • Gerald G. Brown

    (Operations Research Department, Naval Postgraduate School, Monterey, California 93943-5219)

  • Robert F. Dell

    (Operations Research Department, Naval Postgraduate School, Monterey, California 93943-5219)

  • Robert A. Farmer

    (United States Coast Guard, 2100 2nd Street SW, Washington, DC 20593-0001)

Abstract

United States Coast Guard (USCG) districts schedule cutters 180 feet or less in length to weekly statuses ( statuses is USCG jargon for assignments) from which they primarily respond to calls for search and rescue, law enforcement, and pollution control. The First Coast Guard District, based in Boston, has one of the largest scheduling problems: Each of 16 cutters is assigned weekly to one of six statuses to ensure patrol coverage, enforce equitable distribution of patrols, and honor restrictions on consecutive cutter statuses. When we state this quarterly scheduling problem as an elastic mixed-integer linear program, we obtain face-valid schedules—superior to manually prepared schedules for all measures of effectiveness considered—within a few minutes on a personal computer. Initial acceptance of the model was hampered by disruptive schedule revisions that resulted from minor changes in input. Modifications to preserve run-to-run persistence of solutions have brought success.

Suggested Citation

  • Gerald G. Brown & Robert F. Dell & Robert A. Farmer, 1996. "Scheduling Coast Guard District Cutters," Interfaces, INFORMS, vol. 26(2), pages 59-72, April.
    • Handle: RePEc:inm:orinte:v:26:y:1996:i:2:p:59-72
    DOI: 10.1287/inte.26.2.59
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    Citations

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    Cited by:

    1. Gerald G. Brown & Walter C. DeGrange & Wilson L. Price & Anton A. Rowe, 2017. "Scheduling combat logistics force replenishments at sea for the US Navy," Naval Research Logistics (NRL), John Wiley & Sons, vol. 64(8), pages 677-693, December.
    2. Marielle Christiansen & Kjetil Fagerholt & David Ronen, 2004. "Ship Routing and Scheduling: Status and Perspectives," Transportation Science, INFORMS, vol. 38(1), pages 1-18, February.
    3. Günay Uzun & Metin Dağdeviren & Mehmet Kabak, 2016. "Determining the Distribution of Coast Guard Vessels," Interfaces, INFORMS, vol. 46(4), pages 297-314, August.
    4. Michael R. Wagner & Zinovy Radovilsky, 2012. "Optimizing Boat Resources at the U.S. Coast Guard: Deterministic and Stochastic Models," Operations Research, INFORMS, vol. 60(5), pages 1035-1049, October.
    5. Gerald G. Brown & Kelly J. Cormican & Siriphong Lawphongpanich & Daniel B. Widdis, 1997. "Optimizing submarine berthing with a persistence incentive," Naval Research Logistics (NRL), John Wiley & Sons, vol. 44(4), pages 301-318, June.
    6. Amin Akbari & Ronald Pelot & H. A. Eiselt, 2018. "A modular capacitated multi-objective model for locating maritime search and rescue vessels," Annals of Operations Research, Springer, vol. 267(1), pages 3-28, August.
    7. Javier Salmerón & Jeffrey Kline & Greta Spitz Densham, 2011. "Optimizing Schedules for Maritime Humanitarian Cooperative Engagements from a United States Navy Sea Base," Interfaces, INFORMS, vol. 41(3), pages 238-253, June.
    8. Paul A. Chircop & Timothy J. Surendonk & Menkes H. L. van den Briel & Toby Walsh, 2022. "On routing and scheduling a fleet of resource-constrained vessels to provide ongoing continuous patrol coverage," Annals of Operations Research, Springer, vol. 312(2), pages 723-760, May.

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