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.
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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
Ahuja RK, Cunha CB, Sahin G (2005) Network models in railroad planning and scheduling. Tutorials in Operations Research 1:54–101
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
Caprara A, Fischetti M, Toth P (2002) Modeling and solving the train timetabling problem. Oper Res 50:851–861
Carey M, Crawford I (2007) Scheduling trains on a network of busy complex stations. Transp Res B Methodol 41:159–178
Carey M, Lockwood D (1995) A model, algorithms and strategy for train pathing. J Oper Res Soc 46:988–1005
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
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
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
Christiansen M, Fagerholt K, Nygreen B, Ronen D (2013) Ship routing and scheduling in the new millennium. Eur J Oper Res 228:467–483
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
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
Cordeau J-F, Toth P, Vigo D (1998) A survey of optimization models for train routing and scheduling. Transp Sci 32:380–404
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
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
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
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
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
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
Imai A, Nishimura E, Papadimitriou S (2003) Berth allocation with service priority. Transp Res B Methodol 37:437–457
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
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
Lang N, Veenstra A (2010) A quantitative analysis of container vessel arrival planning strategies. OR Spectrum 32:477–499
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
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
Lim A (1998) The berth planning problem. Oper Res Lett 22:105–110
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
Mavrakis D, Kontinakis N (2008) A queueing model of maritime traffic in Bosporus Straits. Simul Model Pract Theory 16:315–328
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
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
Nosengo N (2003) Venice floods: SAVE OUR CITY!. Nature 424:608–609
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
Petersen ER, Taylor AJ (1988) An optimal scheduling system for the Welland Canal. Transp Sci 22:173–185
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
Saha JL (1970) An algorithm for bus scheduling problems. Oper Res Q 21:463–474
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
Tang LC, Low JMW, Lam SW (2011) Understanding port choice behavior—a network perspective. Networks and Spatial Economics 11(1):65–82
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
Ulusçu ÖS, Öbaş B, Altıok T, Or I, Yılmaz T (2009) Transit vessel scheduling in the Strait of Istanbul. J Navig 62:59–77
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
Wang S, Meng Q (2012) Robust schedule design for liner shipping services. Transportation Research Part E: Logistics and Transportation Review 48:1093–1106
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
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).
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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
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DOI: https://doi.org/10.1007/s11067-017-9350-5