Abstract
In this paper we address the in-port ship scheduling and tug assignment problem. This problem aims to determine a schedule of ship movements, and their escorting tugs, within a canal harbor. We formulate the problem as a Boolean satisfiability problem. In particular, we deal with canal-harbors, as this kind of harbors present strict constraints, e.g., on safety distance. We consider the Port of Venice, a medium size Italian harbor, as a case study.
Access this chapter
Tax calculation will be finalised at checkout
Purchases are for personal use only
References
Bierwirth, C., Meisel, F.: A survey of berth allocation and quay crane scheduling problems in container terminals. Eur. J. Oper. Res. 202(3), 615–627 (2010)
Bussieck, M.R., Winter, T., Zimmermann, U.T.: Discrete optimization in public rail transport. Math. Program. 79(1), 415–444 (1997)
Canestrelli, E., Corazza, M., De Nadai, G., Pesenti, R.: Managing the ship movements in the port of Venice. Netw. Spat. Econ. 17(3), 861–887 (2017)
Carlo, H.J., Vis, I.F.A., Roodbergen, K.J.: Seaside operations in container terminals: literature overview, trends, and research directions. Flex. Serv. Manuf. J. 27(2), 224–262 (2015)
Garey, M.R., Johnson, D.S.: Computers and Intractability: A Guide to the Theory of NP-Completeness. Freeman, New York (1979)
Gharehgozli, A.H., Roy, D., de Koster, R.: Sea container terminals: new technologies and or models. Maritime Econ. Logist. 18(2), 103–140 (2016)
Lardeux, F., Saubion, F., Hao, J.K.: GASAT: A genetic local search algorithm for the satisfiability problem. Evol. Comput. 14(2), 223–253 (2006)
Pellegrini, P., Marlière, G., Pesenti, R., Rodriguez, J.: Recife-milp: An effective milp-based heuristic for the real-time railway traffic management problem. IEEE Trans. Intell. Transp. Syst. 16(5), 2609–2619 (2015)
Pellegrini, P., di Tollo, G., Pesenti, R.: Scheduling ships movements within a canal harbor. Soft Comput. (2018). https://doi.org/10.1007/s00500-018-3469-2
Piu, F., Speranza, M.G.: The locomotive assignment problem: a survey on optimization models. Int. Trans. Oper. Res. 21(3), 327–352 (2014)
di Tollo, G., Lardeux, F., Maturana, J., Saubion, F.: An experimental study of adaptive control for evolutionary algorithms. Appl. Soft Comput. 35, 359–372 (2015)
Vaidyanathan, B., Ahuja, R.K., Liu, J., Shughart, L.A.: Real-life locomotive planning: new formulations and computational results. Transp. Res. B Methodol. 42(2), 147–168 (2008)
Wang, X., Arnesen, M.J., Fagerholt, K., Gjestvang, M., Thun, K.: A two-phase heuristic for an in-port ship routing problem with tank allocation. Comput. Oper. Res. 91, 37–47 (2018)
Xu, X., Li, C.L., Xu, Z.: Integrated train timetabling and locomotive assignment. Transp. Res. B: Methodol. 117, 573–593 (2018)
Zhang, X., Lin, J., Guo, Z., Liu, T.: Vessel transportation scheduling optimization based on channel-berth coordination. Ocean Eng. 112, 145–152 (2016)
Zhen, L., Liang, Z., Zhuge, D., Lee, L.H., Chew, E.P.: Daily berth planning in a tidal port with channel flow control. Transp. Res. B Methodol. 106, 193–217 (2017)
Acknowledgements
This study was partially funded by the “Smart PORt Terminals - SPORT” MIUR-PRIN project (grant number: 2015XAPRKF) financed by the Italian state. The study was partially developed within the Centro Studi su Economia e Management della Portualità of Università Ca’ Foscari, Venezia.
Author information
Authors and Affiliations
Corresponding author
Editor information
Editors and Affiliations
Rights and permissions
Copyright information
© 2019 Springer Nature Switzerland AG
About this chapter
Cite this chapter
Tollo, G.d., Pesenti, R., Petris, M. (2019). Integrating Ship Movement Scheduling and Tug Assignment Within a Canal Harbor. In: Paolucci, M., Sciomachen, A., Uberti, P. (eds) Advances in Optimization and Decision Science for Society, Services and Enterprises. AIRO Springer Series, vol 3. Springer, Cham. https://doi.org/10.1007/978-3-030-34960-8_2
Download citation
DOI: https://doi.org/10.1007/978-3-030-34960-8_2
Published:
Publisher Name: Springer, Cham
Print ISBN: 978-3-030-34959-2
Online ISBN: 978-3-030-34960-8
eBook Packages: Mathematics and StatisticsMathematics and Statistics (R0)