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Solving a stochastic inland waterway port management problem using a parallelized hybrid decomposition algorithm

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  • Aghalari, Amin
  • Nur, Farjana
  • Marufuzzaman, Mohammad

Abstract

This study proposes to develop a mathematical model that captures and appropriately optimizes a number of realistic features (e.g., barge/towboat assignments, maintenance, and availability decisions) for the design and management of an inland waterway transportation network under stochastic commodity supply and water level fluctuations scenarios. To efficiently solve this challenging NP-hard problem, we propose to develop a highly customized parallelized hybrid decomposition algorithm that combines Sample Average Approximation with an enhanced Progressive Hedging and Nested Decomposition algorithm. Computational results indicate that the proposed algorithm is capable of producing high quality solutions consistently within a reasonable amount of time. Finally, a real-life case study is constructed by utilizing the inland waterway transportation network along the Mississippi River. Through multiple experimentations, a number of managerial insights are drawn that magnifies the impact of different key input parameters on the overall inland waterway port operations.

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  • Aghalari, Amin & Nur, Farjana & Marufuzzaman, Mohammad, 2021. "Solving a stochastic inland waterway port management problem using a parallelized hybrid decomposition algorithm," Omega, Elsevier, vol. 102(C).
    • Handle: RePEc:eee:jomega:v:102:y:2021:i:c:s0305048320306708
    DOI: 10.1016/j.omega.2020.102316
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    1. Jean-Paul Watson & David Woodruff, 2011. "Progressive hedging innovations for a class of stochastic mixed-integer resource allocation problems," Computational Management Science, Springer, vol. 8(4), pages 355-370, November.
    2. Michel L. Balinski, 1961. "Fixed‐cost transportation problems," Naval Research Logistics Quarterly, John Wiley & Sons, vol. 8(1), pages 41-54, March.
    3. T. L. Magnanti & R. T. Wong, 1981. "Accelerating Benders Decomposition: Algorithmic Enhancement and Model Selection Criteria," Operations Research, INFORMS, vol. 29(3), pages 464-484, June.
    4. Christiansen, Marielle & Fagerholt, Kjetil & Flatberg, Truls & Haugen, Øyvind & Kloster, Oddvar & Lund, Erik H., 2011. "Maritime inventory routing with multiple products: A case study from the cement industry," European Journal of Operational Research, Elsevier, vol. 208(1), pages 86-94, January.
    5. Poudel, Sushil Raj & Marufuzzaman, Mohammad & Bian, Linkan, 2016. "A hybrid decomposition algorithm for designing a multi-modal transportation network under biomass supply uncertainty," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 94(C), pages 1-25.
    6. R. T. Rockafellar & Roger J.-B. Wets, 1991. "Scenarios and Policy Aggregation in Optimization Under Uncertainty," Mathematics of Operations Research, INFORMS, vol. 16(1), pages 119-147, February.
    7. Zhen, Lu & Wang, Kai & Wang, Shuaian & Qu, Xiaobo, 2018. "Tug scheduling for hinterland barge transport: A branch-and-price approach," European Journal of Operational Research, Elsevier, vol. 265(1), pages 119-132.
    8. Baroud, Hiba & Barker, Kash & Ramirez-Marquez, Jose E. & Rocco S., Claudio M., 2014. "Importance measures for inland waterway network resilience," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 62(C), pages 55-67.
    9. Kuzmicz, Katarzyna Anna & Pesch, Erwin, 2019. "Approaches to empty container repositioning problems in the context of Eurasian intermodal transportation," Omega, Elsevier, vol. 85(C), pages 194-213.
    10. Zhang, M. & Janic, M. & Tavasszy, L.A., 2015. "A freight transport optimization model for integrated network, service, and policy design," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 77(C), pages 61-76.
    11. Wiegmans, Bart & Witte, Patrick, 2017. "Efficiency of inland waterway container terminals: Stochastic frontier and data envelopment analysis to analyze the capacity design- and throughput efficiency," Transportation Research Part A: Policy and Practice, Elsevier, vol. 106(C), pages 12-21.
    12. Aghalari, Amin & Nur, Farjana & Marufuzzaman, Mohammad, 2020. "A Bender’s based nested decomposition algorithm to solve a stochastic inland waterway port management problem considering perishable product," International Journal of Production Economics, Elsevier, vol. 229(C).
    13. Lara, Cristiana L. & Mallapragada, Dharik S. & Papageorgiou, Dimitri J. & Venkatesh, Aranya & Grossmann, Ignacio E., 2018. "Deterministic electric power infrastructure planning: Mixed-integer programming model and nested decomposition algorithm," European Journal of Operational Research, Elsevier, vol. 271(3), pages 1037-1054.
    14. Yossiri Adulyasak & Jean-François Cordeau & Raf Jans, 2015. "Benders Decomposition for Production Routing Under Demand Uncertainty," Operations Research, INFORMS, vol. 63(4), pages 851-867, August.
    15. Alfandari, Laurent & Davidović, Tatjana & Furini, Fabio & Ljubić, Ivana & Maraš, Vladislav & Martin, Sébastien, 2019. "Tighter MIP models for Barge Container Ship Routing," Omega, Elsevier, vol. 82(C), pages 38-54.
    16. Chen, Chien-Wei & Fan, Yueyue, 2012. "Bioethanol supply chain system planning under supply and demand uncertainties," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 48(1), pages 150-164.
    17. DeVuyst, Eric & Wilson, William W. & Dahl, Bruce, 2009. "Longer-term forecasting and risks in spatial optimization models: The world grain trade," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 45(3), pages 472-485, May.
    18. Al-Khayyal, Faiz & Hwang, Seung-June, 2007. "Inventory constrained maritime routing and scheduling for multi-commodity liquid bulk, Part I: Applications and model," European Journal of Operational Research, Elsevier, vol. 176(1), pages 106-130, January.
    19. Furkan Oztanriseven & Heather Nachtmann, 2017. "Economic impact analysis of inland waterway disruption response," The Engineering Economist, Taylor & Francis Journals, vol. 62(1), pages 73-89, January.
    20. Santoso, Tjendera & Ahmed, Shabbir & Goetschalckx, Marc & Shapiro, Alexander, 2005. "A stochastic programming approach for supply chain network design under uncertainty," European Journal of Operational Research, Elsevier, vol. 167(1), pages 96-115, November.
    21. Wang, Shuaian & Meng, Qiang, 2015. "Robust bunker management for liner shipping networks," European Journal of Operational Research, Elsevier, vol. 243(3), pages 789-797.
    22. P. Simões & R.C. Marques, 2010. "Seaport performance analysis using robust non-parametric efficiency estimators," Transportation Planning and Technology, Taylor & Francis Journals, vol. 33(5), pages 435-451, June.
    23. Zhijia Tan & Yadong Wang & Qiang Meng & Zhixue Liu, 2018. "Joint Ship Schedule Design and Sailing Speed Optimization for a Single Inland Shipping Service with Uncertain Dam Transit Time," Service Science, INFORMS, vol. 52(6), pages 1570-1588, December.
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    2. Golak, Julian Arthur Pawel & Defryn, Christof & Grigoriev, Alexander, 2022. "Optimizing fuel consumption on inland waterway networks: Local search heuristic for lock scheduling," Omega, Elsevier, vol. 109(C).

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