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Mathematical programming models for lock scheduling with an emission objective

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  • Passchyn, Ward
  • Briskorn, Dirk
  • Spieksma, Frits C.R.

Abstract

We investigate the scheduling of series of consecutive locks. This setting occurs naturally along canals and waterways. Our contribution is to (i) provide two distinct mathematical programming formulations and compare them empirically, (ii) investigate the trade-off between reducing flow time and reducing emissions, and (iii) compare the results of the integrated model to those of a heuristic scheduling the locks separately. Our findings confirm that integrated scheduling of consecutive locks can reduce flow time significantly, and reveal that both model formulations have their merits when compared to each other.

Suggested Citation

  • Passchyn, Ward & Briskorn, Dirk & Spieksma, Frits C.R., 2016. "Mathematical programming models for lock scheduling with an emission objective," European Journal of Operational Research, Elsevier, vol. 248(3), pages 802-814.
  • Handle: RePEc:eee:ejores:v:248:y:2016:i:3:p:802-814
    DOI: 10.1016/j.ejor.2015.09.012
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    References listed on IDEAS

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    1. Verstichel, J. & De Causmaecker, P. & Spieksma, F.C.R. & Vanden Berghe, G., 2014. "Exact and heuristic methods for placing ships in locks," European Journal of Operational Research, Elsevier, vol. 235(2), pages 387-398.
    2. E. R. Petersen & A. J. Taylor, 1988. "An Optimal Scheduling System for the Welland Canal," Transportation Science, INFORMS, vol. 22(3), pages 173-185, August.
    3. L D Smith & D C Sweeney & J F Campbell, 2009. "Simulation of alternative approaches to relieving congestion at locks in a river transportion system," Journal of the Operational Research Society, Palgrave Macmillan;The OR Society, vol. 60(4), pages 519-533, April.
    4. Nauss, Robert M., 2008. "Optimal sequencing in the presence of setup times for tow/barge traffic through a river lock," European Journal of Operational Research, Elsevier, vol. 187(3), pages 1268-1281, June.
    5. Douglas Smith, L. & Nauss, Robert M. & Mattfeld, Dirk Christian & Li, Jian & Ehmke, Jan F. & Reindl, M., 2011. "Scheduling operations at system choke points with sequence-dependent delays and processing times," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 47(5), pages 669-680, September.
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    Cited by:

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    2. Ward Passchyn & Frits C. R. Spieksma, 2019. "Scheduling parallel batching machines in a sequence," Journal of Scheduling, Springer, vol. 22(3), pages 335-357, June.
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    6. Wenjie Li & Jialing Dai & Yi Xiao & Shengfa Yang & Chenpeng Song, 2021. "Estimating waterway freight demand at Three Gorges ship lock on Yangtze River by backpropagation neural network modeling," Maritime Economics & Logistics, Palgrave Macmillan;International Association of Maritime Economists (IAME), vol. 23(3), pages 495-521, September.
    7. 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).
    8. Nicolas Pinson & Frits C. R. Spieksma, 2019. "Online interval scheduling on two related machines: the power of lookahead," Journal of Combinatorial Optimization, Springer, vol. 38(1), pages 224-253, July.
    9. Buchem, Moritz & Golak, Julian Arthur Pawel & Grigoriev, Alexander, 2022. "Vessel velocity decisions in inland waterway transportation under uncertainty," European Journal of Operational Research, Elsevier, vol. 296(2), pages 669-678.
    10. Ji, Bin & Zhang, Dezhi & Yu, Samson S. & Zhang, Binqiao, 2021. "Optimally solving the generalized serial-lock scheduling problem from a graph-theory-based multi-commodity network perspective," European Journal of Operational Research, Elsevier, vol. 288(1), pages 47-62.
    11. Ji, Bin & Zhang, Dezhi & Zhang, Zheng & Yu, Samson S. & Van Woensel, Tom, 2022. "The generalized serial-lock scheduling problem on inland waterway: A novel decomposition-based solution framework and efficient heuristic approach," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 168(C).
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