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Modeling the Increased Complexity of New York City's Refuse Marine Transport System

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  • Octavio Richetta

    (College of Management, University of Massachusetts--Boston, Boston, MA 02125)

  • Richard C. Larson

    (Massachusetts Institute of Technology, Boston, MA 02139)

Abstract

The New York City Department of Sanitation operates the world's largest refuse marine transport system. Waste trucks unload their cargo at land-based transfer stations where refuse is placed in barges and then towed by tugboats to the Fresh Kills Landfill in Staten Island. In the early 1980s, the city commissioned the development of a computer-based model for use in fleet sizing and operations planning. As a result of the complexities introduced by environmental regulation and technological innovation, the marine transport system operations changed and the existing model became obsolete. Based on the success achieved with the first model in 1993, the city commissioned the development of a new model. In this paper, we present a PC-based model developed to meet the increased complexity of the system. Analysis performed for validation and calibration of the model demonstrates that it tracks well the operations of the real system. We illustrate through a detailed design exercise how to use the model to configure the system in a way that meets the requirements of the refuse marine transport system.

Suggested Citation

  • Octavio Richetta & Richard C. Larson, 1997. "Modeling the Increased Complexity of New York City's Refuse Marine Transport System," Transportation Science, INFORMS, vol. 31(3), pages 272-293, August.
    • Handle: RePEc:inm:ortrsc:v:31:y:1997:i:3:p:272-293
    DOI: 10.1287/trsc.31.3.272
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    Cited by:

    1. Ioannis Fragkos & Bert De Reyck, 2016. "Improving the Maritime Transshipment Operations of the Noble Group," Interfaces, INFORMS, vol. 46(3), pages 203-217, April.
    2. Giovanni Pantuso & Kjetil Fagerholt & Stein W. Wallace, 2016. "Uncertainty in Fleet Renewal: A Case from Maritime Transportation," Transportation Science, INFORMS, vol. 50(2), pages 390-407, May.
    3. Hamidreza Eskandari & Ehsan Mahmoodi, 2016. "A simulation-based multi-objective optimization study of the fleet sizing problem in the offshore industry," Maritime Economics & Logistics, Palgrave Macmillan;International Association of Maritime Economists (IAME), vol. 18(4), pages 436-457, December.
    4. Labelle, A. & Langevin, A. & Campbell, J. F., 2002. "Sector design for snow removal and disposal in urban areas," Socio-Economic Planning Sciences, Elsevier, vol. 36(3), pages 183-202, September.
    5. Pantuso, Giovanni & Fagerholt, Kjetil & Hvattum, Lars Magnus, 2014. "A survey on maritime fleet size and mix problems," European Journal of Operational Research, Elsevier, vol. 235(2), pages 341-349.
    6. Fagerholt, Kjetil & Christiansen, Marielle & Magnus Hvattum, Lars & Johnsen, Trond A.V. & Vabø, Thor J., 2010. "A decision support methodology for strategic planning in maritime transportation," Omega, Elsevier, vol. 38(6), pages 465-474, December.
    7. Omar Besbes & Sergei Savin, 2009. "Going Bunkers: The Joint Route Selection and Refueling Problem," Manufacturing & Service Operations Management, INFORMS, vol. 11(4), pages 694-711, February.
    8. Marielle Christiansen & Kjetil Fagerholt & David Ronen, 2004. "Ship Routing and Scheduling: Status and Perspectives," Transportation Science, INFORMS, vol. 38(1), pages 1-18, February.
    9. Richard Charles Larson, 2002. "Public Sector Operations Research: A Personal Journey," Operations Research, INFORMS, vol. 50(1), pages 135-145, February.
    10. Shyshou, Aliaksandr & Gribkovskaia, Irina & Barceló, Jaume, 2010. "A simulation study of the fleet sizing problem arising in offshore anchor handling operations," European Journal of Operational Research, Elsevier, vol. 203(1), pages 230-240, May.

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