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Budgeting maintenance dredging projects under uncertainty to improve the inland waterway network performance

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  • Ahadi, Khatereh
  • Sullivan, Kelly M.
  • Mitchell, Kenneth Ned

Abstract

We model the problem of budgeting and selecting inland maintenance dredging projects to maximize the value of commodities that can be transported without disruption through the inland waterway system. We develop a heuristic to solve our stochastic optimization model and demonstrate that, by incorporating uncertainty in the amount of reactive (i.e., emergency) dredging, our model yields improved solutions as compared to related deterministic optimization models in the literature. We apply our model to provide a detailed analysis of U.S. waterway network.

Suggested Citation

  • Ahadi, Khatereh & Sullivan, Kelly M. & Mitchell, Kenneth Ned, 2018. "Budgeting maintenance dredging projects under uncertainty to improve the inland waterway network performance," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 119(C), pages 63-87.
    • Handle: RePEc:eee:transe:v:119:y:2018:i:c:p:63-87
    DOI: 10.1016/j.tre.2018.08.013
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    References listed on IDEAS

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    1. J. K. Lenstra & A. H. G. Rinnooy Kan, 1978. "Complexity of Scheduling under Precedence Constraints," Operations Research, INFORMS, vol. 26(1), pages 22-35, February.
    2. Asadabadi, Ali & Miller-Hooks, Elise, 2017. "Optimal transportation and shoreline infrastructure investment planning under a stochastic climate future," Transportation Research Part B: Methodological, Elsevier, vol. 100(C), pages 156-174.
    3. G. A. Jones & J. G. Wilson, 1979. "Optimal Scheduling of Jobs on a Transmission Network," Management Science, INFORMS, vol. 25(1), pages 98-104, January.
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    Cited by:

    1. Feng, Xuejun & Hu, Sangen & Gu, Weihua & Jin, Xin & Lu, Yuan, 2020. "A simulation-based approach for assessing seaside infrastructure improvement measures for large marine crude oil terminals," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 142(C).
    2. Bian, Zheyong & Bai, Yun & Douglas, W. Scott & Maher, Ali & Liu, Xiang, 2022. "Multi-year planning for optimal navigation channel dredging and dredged material management," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 159(C).
    3. Lúcio Carlos Pinheiro Campos Filho & Nelio Moura de Figueiredo & Cláudio José Cavalcante Blanco & Maisa Sales Gama Tobias & Paulo Afonso, 2024. "Machine Learning for the Sustainable Management of Depth Prediction and Load Optimization in River Convoys: An Amazon Basin Case Study," Sustainability, MDPI, vol. 16(19), pages 1-22, September.
    4. Mahmoudzadeh, Ahmadreza & Khodakarami, Mohammadadel & Ma, Chaolun & Mitchell, Kenneth Ned & Wang, Xiubin Bruce & Zhang, Yunlong, 2021. "Waterway maintenance budget allocation in a multimodal network," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 146(C).

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