Skip to main content
Log in

Managing the Ship Movements in the Port of Venice

  • Published:
Networks and Spatial Economics Aims and scope Submit manuscript

Abstract

The new mobile gates at the inlets of the Venice lagoon and the new previous environmental laws issued in response of the Costa Concordia wreckage in 2012 have forced the Port Authority of Venice to rethink the harbor activities. In this paper, we tackle the Port Scheduling Problem that the Port Authority faces in scheduling both ships’ and tugs’ movements within its canal harbor in this new context. We introduce the problem, explain which data it needs, and provide the description of an original heuristic algorithm for its solution. Finally, we present some practical applications.

This is a preview of subscription content, log in via an institution to check access.

Access this article

Price excludes VAT (USA)
Tax calculation will be finalised during checkout.

Instant access to the full article PDF.

Fig. 1
Fig. 2
Fig. 3
Fig. 4
Fig. 5
Fig. 6

Similar content being viewed by others

References

  • Acuna-Agost R, Michelon P, Feillet D, Gueye S (2011) SAPI: Statistical Analysis of propagation of incidents. a new approach for rescheduling trains after disruptions. Eur J Oper Res 215:227–243

    Article  Google Scholar 

  • Ahuja RK, Cunha CB, Sahin G (2005) Network models in railroad planning and scheduling. Tutorials in Operations Research 1:54–101

    Google Scholar 

  • Bagozzi RP (2007) The legacy of the technology acceptance model and a proposal for a paradigm shiftm. J Assoc Inf Syst 8. art.12

  • Cai X, Goh C, Mees AI (1998) Greedy heuristics for rapid scheduling of trains on a single track. IIE Trans 30:481–493

    Article  Google Scholar 

  • Caprara A, Fischetti M, Toth P (2002) Modeling and solving the train timetabling problem. Oper Res 50:851–861

    Article  Google Scholar 

  • Carey M, Crawford I (2007) Scheduling trains on a network of busy complex stations. Transp Res B Methodol 41:159–178

    Article  Google Scholar 

  • Carey M, Lockwood D (1995) A model, algorithms and strategy for train pathing. J Oper Res Soc 46:988–1005

    Article  Google Scholar 

  • Caschili S, Medda F, Parola F, Ferrari C (2014) An analysis of shipping agreements: The cooperative container network. Networks and Spatial Economics 14 (3):357–377

    Article  Google Scholar 

  • Chang C-C, Wang C-M (2012) Evaluating the effects of green port policy: Case study of Kaohsiung harbor in Taiwan. Transp Res Part D Transp Environ 17:185–189

    Article  Google Scholar 

  • Chang Y-T, Song Y, Roh Y (2013) Assessing greenhouse gas emissions from port vessel operations at the Port of Incheon. Transp Res Part D Transp Environ 25:1–4

    Article  Google Scholar 

  • Christiansen M, Fagerholt K, Nygreen B, Ronen D (2013) Ship routing and scheduling in the new millennium. Eur J Oper Res 228:467–483

    Article  Google Scholar 

  • Corbett JJ, Wang H, Winebrake JJ (2009) The effectiveness and costs of speed reductions on emissions from international shipping. Transp Res Part D Transp Environ 14:593–598

    Article  Google Scholar 

  • Cordeau J-F, Laporte G, Legato P, Moccia L (2005) Models and tabu search heuristics for the berth-allocation problem. Transp Sci 39:526–538

    Article  Google Scholar 

  • Cordeau J-F, Toth P, Vigo D (1998) A survey of optimization models for train routing and scheduling. Transp Sci 32:380–404

    Article  Google Scholar 

  • D’Ariano A, Pranzo M (2009) An advanced real-time train dispatching system for minimizing the propagation of delays in a dispatching area under severe disturbances. Networks and Spatial Economics 9:63–84

    Article  Google Scholar 

  • Du Y, Chen Q, Lam JSL, Xu Y, Cao JX (2015) Modeling the impacts of tides and the virtual arrival policy in berth allocation. Transp Sci 49:939–956

    Article  Google Scholar 

  • Franzese LAG, Abdenur LO, Botter RC, Starks D, Cano AR (2011) Simulating the Panama canal: present and future. Inproceedings of the 2004 winter simulation conference 2:1835–1838

    Google Scholar 

  • Gatica RA, Miranda PA (2011) Special issue on latin-american research: a time based discretization approach for ship routing and scheduling with variable speed. Networks and Spatial Economics 11(3):465–485

    Article  Google Scholar 

  • Gharehgozli AH, Roy D, de Koste R (2015) Sea container terminals: New technologies and OR models. Maritime Economics & Logistics 18:103–140

  • Golias MM, Boile M, Theofanis S (2010) A lamda-optimal based heuristic for the berth scheduling problem. Transp Res C Emerg Technol 18:794–806

    Article  Google Scholar 

  • Golias MM, Saharidis GK, Boile M, Theofanis S, Ierapetritou MG (2009) The berth allocation problem: Optimizing vessel arrival time. Maritime Economics & Logistics 11:358–377

    Article  Google Scholar 

  • Imai A, Nishimura E, Papadimitriou S (2003) Berth allocation with service priority. Transp Res B Methodol 37:437–457

    Article  Google Scholar 

  • Imai J-T, Zhang A, Nishimura E, Papadimitriou S (2007) The berth allocation problem with service time and delay time objectives. Maritime Economics and Logistics 9:269–290

    Article  Google Scholar 

  • Kellerer H, Tautenhahn T, Woeginger G (1999) Approximability and nonapproximability results for minimizing total flow time on a single machine. SIAM J Comput 28:1155–1166

    Article  Google Scholar 

  • Lang N, Veenstra A (2010) A quantitative analysis of container vessel arrival planning strategies. OR Spectrum 32:477–499

    Article  Google Scholar 

  • Legris P, Ingham J, Collerette P (2003) Why do people use information technology? a critical review of the technology acceptance model. Information & Management 40:191–204

    Article  Google Scholar 

  • Liao C-H, Tseng P -H, Cullinane K, Lu C-S (2010) The impact of an emerging port on the carbon dioxide emissions of inland container transport: An empirical study of Taipei port. Energy Policy 38:5251–5257

    Article  Google Scholar 

  • Lim A (1998) The berth planning problem. Oper Res Lett 22:105–110

    Article  Google Scholar 

  • Lohatepanont M, Kongsermsup V (2012) Model and algorithm for bulk cargo ship routing and scheduling under port congestion condition TRB 91st Annual Meeting Compendium of Papers Transportation Research Board

  • Lusby RM, Larsen J, Ehrgott M, Ryan D (2011) Railway track allocation: models and methods. OR Spectrum 33:843–883

    Article  Google Scholar 

  • Mavrakis D, Kontinakis N (2008) A queueing model of maritime traffic in Bosporus Straits. Simul Model Pract Theory 16:315–328

    Article  Google Scholar 

  • Meng Q, Wang S, Andersson H, Thun K (2013) Containership routing and scheduling in liner shipping: Overview and future research directions. Transp Sci 48:265–280

    Article  Google Scholar 

  • Nauss RM (2008) Optimal sequencing in the presence of setup times for tow/barge traffic through a river lock. Eur J Oper Res 187:1268–1281

    Article  Google Scholar 

  • Nosengo N (2003) Venice floods: SAVE OUR CITY!. Nature 424:608–609

    Article  Google Scholar 

  • Palacio A, Adenso-Díaz B, Lozano S, Furió S (2016) Bicriteria optimization model for locating maritime container depots: Application to the port of valencia. Networks and Spatial Economics 16(1):331–348

    Article  Google Scholar 

  • Petersen ER, Taylor AJ (1988) An optimal scheduling system for the Welland Canal. Transp Sci 22:173–185

    Article  Google Scholar 

  • Qu Y, Bektaṡ T, Bennell J (2016) Sustainability si: Multimode multicommodity network design model for intermodal freight transportation with transfer and emission costs. Networks and Spatial Economics 16(1):303–329

    Article  Google Scholar 

  • Saha JL (1970) An algorithm for bus scheduling problems. Oper Res Q 21:463–474

    Article  Google Scholar 

  • Schröder-Hinrichs J-U, Hollnagel E, Baldauf M (2012) From Titanic to Costa Concordia - a century of lessons not learned. WMU J Marit Aff 11:151–167

    Article  Google Scholar 

  • Tang LC, Low JMW, Lam SW (2011) Understanding port choice behavior—a network perspective. Networks and Spatial Economics 11(1):65–82

    Article  Google Scholar 

  • Törnquist J (2006) Computer-based decision support for railway traffic scheduling and dispatching: A review of models and algorithms. In: Kroon LG, Möhring RH (eds) 5th Workshop on Algorithmic Methods and Models for Optimization of Railways. Schloss Dagstuhl, D

  • Ulusçu ÖS, Altıok T (2009) Waiting time approximation in single-class queueing systems with multiple types of interruptions: modeling congestion at waterways entrances. Ann Oper Res 172:291– 313

    Article  Google Scholar 

  • Ulusçu ÖS, Öbaş B, Altıok T, Or I, Yılmaz T (2009) Transit vessel scheduling in the Strait of Istanbul. J Navig 62:59–77

    Article  Google Scholar 

  • Vaidyanathan B, Ahuja RK (2015) Locomotive scheduling problem. In: Patty BW (ed) Handbook of Operations Research Applications at Railroads, vol 222. Springer, NY, pp 43–56

  • Verstichel J, Causmaecker PD, Berghe GV (2011) Scheduling algorithms for the lock scheduling problem. Procedia Soc Behav Sci 20:806–815

    Article  Google Scholar 

  • Wang S, Meng Q (2012) Robust schedule design for liner shipping services. Transportation Research Part E: Logistics and Transportation Review 48:1093–1106

    Article  Google Scholar 

  • Zhou X, Zhong M (2007) Single-track train timetabling with guaranteed optimality: branch-and-bound algorithms with enhanced lower bounds. Transp Res B Methodol 41:320–341

    Article  Google Scholar 

Download references

Acknowledgments

This research has been partially funded within the EU project “The Adriatic port community - APC” (code: 111/2009; CUP: F72H11000000007; CIG: 3725704433) and within the Italian MIUR-PRIN project “Smart PORt Terminals - SPORT (code: #2015XAPRKF).

Author information

Authors and Affiliations

Authors

Corresponding author

Correspondence to Marco Corazza.

Rights and permissions

Reprints and permissions

About this article

Check for updates. Verify currency and authenticity via CrossMark

Cite this article

Canestrelli, E., Corazza, M., De Nadai, G. et al. Managing the Ship Movements in the Port of Venice. Netw Spat Econ 17, 861–887 (2017). https://doi.org/10.1007/s11067-017-9350-5

Download citation

  • Published:

  • Issue Date:

  • DOI: https://doi.org/10.1007/s11067-017-9350-5

Keywords

Navigation