Skip to main content
Log in

Sea container terminals: New technologies and OR models

  • Original Article
  • Published:
Maritime Economics & Logistics Aims and scope

Abstract

Owing to a rapid growth in world trade and a large increase in the flow of containerized goods, sea container terminals play a vital role in globe-spanning supply chains. Container terminals should be able to handle large ships, with large call sizes within the shortest time possible, and at competitive rates. In response, terminal operators, shipping lines and port authorities are investing in new technologies to improve container handling and operational efficiency. Container terminals face challenging research problems that have received much attention from the academic community. The focus of this article is on highlighting recent developments in container terminals, which can be categorized into two areas: (i) innovative container terminal technologies and (ii) new OR directions and models for existing research areas. By choosing this focus, we complement existing reviews on container terminal operations.

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.

Figure 1
Figure 2
Figure 3
Figure 4
Figure 5
Figure 6
Figure 7
Figure 8
Figure 9

Similar content being viewed by others

References

  • Agarwal, R. and Ergun, Ö. (2008) Ship scheduling and network design for cargo routing in liner shipping. Transportation Science 42 (2): 175–196.

    Google Scholar 

  • Agerschou, H. et al (1983) Planning and Design of Ports and Marine Terminals. Chichester, UK: John Wiley and Sons.

    Google Scholar 

  • Almotairi, B., Flodén, J., Stefansson, G. and Woxenius, J. (2011) Information flows supporting hinterland transportation by rail: Applications in Sweden. Research in Transportation Economics 33 (1): 15–24.

    Google Scholar 

  • Avriel, M., Penn, M. and Shpirer, N. (2000) Container ship stowage problem: Complexity and connection to the coloring of circle graphs. Discrete Applied Mathematics 103 (1–3): 271–279.

    Google Scholar 

  • Bierwirth, C. and Meisel, F. (2009) A fast heuristic for quay crane scheduling with interference con straints. Journal of Scheduling 12 (4): 345–360.

    Google Scholar 

  • Bierwirth, C. and Meisel, F. (2010) A survey of berth allocation and quay crane scheduling problems in container terminals. European Journal of Operational Research 202 (3): 615–627.

    Google Scholar 

  • Boer, C.A. and Saanen, Y.A. (2012) Improving container terminal efficiency through emulation. Journal of Simulation 6 (2012): 267–278.

    Google Scholar 

  • Borgman, B., Van Asperen, E. and Dekker, R. (2010) Online rules for container stacking. OR Spectrum 32 (3): 687–716.

    Google Scholar 

  • Bortfeldt, A. and Forster, F. (2012) A tree search procedure for the container pre-marshalling problem. European Journal of Operational Research 217 (3): 531–540.

    Google Scholar 

  • Brinkmann, B. (2010) Operations Systems of Container Terminals: A Compendious Overview. Berlin/Heidelberg, Germany: Springer, pp. 25–39.

    Google Scholar 

  • Buhrkal, K., Zuglian, S., Ropke, S., Larsen, J. and Lusby, R. (2011) Models for the discrete berth al location problem: A computational comparison. Transportation Research Part E: Logistics and Transportation Review 47 (4): 461–473.

    Google Scholar 

  • Canonaco, P., Legato, P., Rina, M.M. and Musmanno, R. (2008) A queuing network model for the management of berth crane operations. Computers & Operations Research 35 (8): 2432–2446.

    Google Scholar 

  • Cao, Z., Lee, D.H. and Meng, Q. (2008) Deployment strategies of double-rail-mounted gantry crane systems for loading outbound containers in container terminals. International Journal of Production Economics 115 (1): 221–228.

    Google Scholar 

  • Carlo, H.J., Iris, F.A. and Vis, K.J.R. (2014a) Storage yard operations in container terminals: Literature overview, trends, and research directions. European Journal of Operational Research 235 (2): 412–430.

    Google Scholar 

  • Carlo, H.J., Iris, F.A. and Vis, K.J.R. (2014b) Transport operations in container terminals: Literature overview, trends, research directions and classification scheme. European Journal of Operational Research 236 (1): 1–13.

    Google Scholar 

  • Carlo, H.J., Iris, F.A. and Vis, K.J.R. (2013) Seaside operations in container terminals: Literature overview, trends, and research directions. Flexible Services and Manufacturing Journal 1–39, doi: 10.1007/s10696-013-9178-3.

  • Caserta, M., Schwarze, S. and Voß, S. (2009) A new binary description of the blocks relocation problem and benefits in a look ahead heuristic. In: C. Cotta and P. Cowling (eds.) Evolutionary Computation in Combinatorial Optimization, Lecture Notes in Computer Science. Vol. 5482. Berlin/Heidelberg, Germany: Springer, pp. 37–48.

    Google Scholar 

  • Caserta, M., Schwarze, S. and Voß, S. (2012) A mathematical formulation and complexity considerations for the blocks relocation problem. European Journal of Operational Research 219 (1): 96–104.

    Google Scholar 

  • Caserta, M. and Voß, S. (2009a) A cooperative strategy for guiding the corridor method. In: N. Krasnogor, M. Melian-Batista, J. Perez, J. Moreno-Vega and D. Pelta (eds.) Nature Inspired Cooperative Strategies for Optimization (NICSO 2008), Studies in Computational Intelligence. Vol. 236. Berlin/Heidelberg, Germany: Springer, pp. 273–286.

    Google Scholar 

  • Caserta, M. and Voß, S. (2009b) A corridor method-based algorithm for the pre-marshalling problem. In: M. Giacobini et al (eds.) Applications of Evolutionary Computing, Lecture Notes in Computer Science. Vol. 5484 Berlin/Heidelberg: Springer, pp. 788–797.

    Google Scholar 

  • Caserta, M. and Voß, S. (2009c) Corridor selection and fine tuning for the corridor method. In: T. Stutzle (ed.) Learning and Intelligent Optimization, Lecture Notes in Computer Science. Vol. 5851. Berlin/Heidelberg, Germany: Springer, pp. 163–175.

    Google Scholar 

  • Caserta, M., Voß, S. and Sniedovich, M. (2011) Applying the corridor method to a blocks relocation problem. OR Spectrum 33 (4): 915–929.

    Google Scholar 

  • Casey, B. and Kozan, E. (2012) Optimising container storage processes at multimodal terminals. Journal of the Operational Research Society 63 (8): 1126–1142.

    Google Scholar 

  • Chang, D., Jiang, Z., Yan, W. and He, J. (2010) Integrating berth allocation and quay crane assignments. Transportation Research Part E: Logistics and Transportation Review 46 (6): 975–990.

    Google Scholar 

  • Chang, D., Jiang, Z., Yan, W. and He, J. (2011) Developing a dynamic rolling-horizon decision strategy for yard crane scheduling. Advanced Engineering Informatics 25 (3): 485–494.

    Google Scholar 

  • Chen, G., Govindan, K. and Yang, Z. (2013) Managing truck arrivals with time windows to alleviate gate congestion at container terminals. International Journal of Production Economics 141 (1): 179–188.

    Google Scholar 

  • Chen, L. and Langevin, A. (2011) Multiple yard cranes scheduling for loading operations in a container terminal. Engineering Optimization 43 (11): 1205–1221.

    Google Scholar 

  • Chen, G. and Yang, Z. (2010) Optimizing time windows for managing export container arrivals at Chinese container terminals. Maritime Economics & Logistics 12 (1): 111–126.

    Google Scholar 

  • Chen, J.H., Lee, D.H. and Cao, J.X. (2011a) Heuristics for quay crane scheduling at indented berth. Transportation Research Part E: Logistics and Transportation Review 47 (6): 1005–1020.

    Google Scholar 

  • Chen, X., Zhou, X. and List, G.F. (2011b) Using time-varying tolls to optimize truck arrivals at ports. Transportation Research Part E: Logistics and Transportation Review 47 (6): 965–982.

    Google Scholar 

  • Cheung, R.K., Li, C.L. and Lin, W. (2002) Interblock crane deployment in container terminals. Transportation Science 36 (1): 79–93.

    Google Scholar 

  • China Communications construction company. (2010) Three-container spreader. http://en.ccccltd.cn/business/heavymachinerymanufactory/201011/t20101112_1549.html, accessed 4 April 2012.

  • Choo, S., Klabjan, D. and Simchi-Levi, D. (2010) Multiship crane sequencing with yard congestion constraints. Transportation Science 44 (1): 98–115.

    Google Scholar 

  • Cordeau, J.F., Toth, P. and Vigo, D. (1998) A survey of optimization models for train routing and scheduling. Transportation Science 32 (4): 380–404.

    Google Scholar 

  • Crainic, G.T. and Kim, K.H. (2007) Chapter 8 intermodal transportation. In: C. Barnhart and G. Laporte (eds.) Transportation, Handbooks in Operations Research and Management Science. Vol. 14. Elsevier, pp. 467–537.

    Google Scholar 

  • De Castillo, B. and Daganzo, C.F. (1993) Handling strategies for import containers at marine terminals. Transportation Research Part B: Methodological 27 (2): 151–166.

    Google Scholar 

  • De Koster, R., Balk, B.M. and Van Nus, W.T.I. (2009) On using DEA for benchmarking container terminals. International Journal of Operations & Production Management 29 (11): 1140–1155.

    Google Scholar 

  • Dekker, R., Van der Heide, S., Van Asperen, E. and Ypsilantis, P. (2012b) A chassis exchange terminal to reduce truck congestion at container terminals. Flexible Services and Manufacturing Journal 25 (4): 528–542.

    Google Scholar 

  • Dekker, R., Voogd, P. and Asperen, E. (2007) Advanced methods for container stacking. In: K.H. Kim and H.O. Günther (eds.) Container Terminals and Cargo Systems. Berlin/Heidelberg, Germany: Springer, pp. 131–154.

    Google Scholar 

  • Delgado, A., Jensen, R.M., Janstrup, K., Rose, T.H. and Andersen, K.H. (2012) A constraint programming model for fast optimal stowage of container vessel bays. European Journal of Operational Research 220 (1): 251–261.

    Google Scholar 

  • Dorndorf, U. and Schneider, F. (2010) Scheduling automated triple cross-over stacking cranes in a container yard. OR Spectrum 32 (3): 617–632.

    Google Scholar 

  • Douma, A., Schutten, M. and Schuur, P. (2009) Waiting profiles: An efficient protocol for enabling distributed planning of container barge rotations along terminals in the port of rotterdam. Transportation Research Part C: Emerging Technologies 17 (2): 133–148.

    Google Scholar 

  • Douma, A., Schuur, P. and Jagerman, R. (2011a) Degrees of terminal cooperativeness and the efficiency of the barge handling process. Expert Systems with Applications 38 (4): 3580–3589.

    Google Scholar 

  • Douma, A., Schuur, P. and Schutten, M. (2011b) Aligning barge and terminal operations using service time profiles. Flexible Services and Manufacturing Journal 23 (4): 385–421.

    Google Scholar 

  • Drewry. (2011) Container Forecaster. London: Drewery Publications.

  • Du, Y., Chen, Q., Quan, X., Long, L. and Fung, R.Y.K. (2011) Berth allocation considering fuel consumption and vessel emissions. Transportation Research Part E: Logistics and Transportation Review 47 (6): 1021–1037.

    Google Scholar 

  • Europe Container Terminals (ECT). (2012) from ECT: http://www.ect.nl/imagegallery/pages/Gallery.aspx, accessed 4 April 2012.

  • Expósito-Izquierdo, C., Melian-Batista, B. and Moreno-Vega, M. (2012) Pre-marshalling problem: Heuristic solution method and instances generator. Expert Systems with Applications 39 (9): 8337–8349.

    Google Scholar 

  • Ez-Indus. (2012) Ultra high container warehouse system. http://www.ezindus.com/emain.php?page=emenu2&sub=eez_m2, accessed 4 April 2012.

  • Forster, F. and Bortfeldt, A. (2012) A tree search procedure for the container relocation problem. Computers & OR 39 (2): 299–309.

    Google Scholar 

  • Froyland, G., Koch, T., Megow, N., Duane, E. and Wren, H. (2008) Optimizing the landside operation of a container terminal. OR Spectrum 30 (1): 53–75.

    Google Scholar 

  • Gharehgozli, A.H., Laporte, G., Yu, Y. and de Koster, R. (2014a) Scheduling twin yard cranes in a container block. Transportation Science. pp. 1–20 ISSN 0041-1655 (print) ISSN 1526-5447 (online), http://dx.doi.org/10.1287/trsc.2014.0533.

  • Gharehgozli, A.H., Yu, Y., de Koster, R. and Udding, J.T. (2014b) An exact method for scheduling a yard crane. European Journal of Operational Research 235 (2): 431–447.

    Google Scholar 

  • Gharehgozli, A.H., Yu, Y., de Koster, R. and Udding, J.T. (2014c) A decision-tree stacking heuristic for large scale reshuffling problems at a container yard. International Journal of Production Research 52 (9): 2592–2611.

    Google Scholar 

  • Giallombardo, G., Moccia, L., Salani, M. and Vacca, I. (2010) Modeling and solving the tactical berth-allocation problem. Transportation Research Part B: Methodological 44 (2): 232–245.

    Google Scholar 

  • Giebel, F.G. (2003) Massareductie op de horizontale transportwagen van de carrier crane. http://wbmttt.tudelft.nl/rapport/6820e.htm, accessed 4 April 2012.

  • Giuliano, G. and O’Brien, T. (2007) Reducing port-related truck emissions: The terminal gate appointment system at the ports of los angeles and long beach. Transportation Research Part D: Transport and Environment 12 (7): 460–473.

    Google Scholar 

  • Gorman, M., Clarke, J.-P., Gharehgozli, A., Hewitt, M., De Koster, R. and Roy, D. (2014) State of the Practice: A Review of the Application of OR/MS in Freight Transportation. Working Paper.

  • Gottwald Port Technology GmbH. (2012) Automated guided vehicles AGV the future is already here. http://www.gottwald.com/gottwald/site/gottwald/en/products/agv.html, accessed 1 August 2013.

  • Groothedde, B., Ruijgrok, C. and Tavasszy, L. (2005) Towards collaborative, intermodal hub networks: A case study in the fast moving consumer goods market. Transportation Research Part E: Logistics and Transportation Review 41 (6): 567–583.

    Google Scholar 

  • Guan, L. and Liu, R. (2009) Container terminal gate appointment system optimization. Maritime Economics & Logistics 11 (4): 378–398.

    Google Scholar 

  • Gue, K.R., Ivanovi c, G. and Russell, D.M. (2012) A unit-load warehouse with multiple pickup and deposit points and non-traditional aisles. Transportation Research Part E: Logistics and Transportation Review 48 (4): 795–806.

    Google Scholar 

  • Gue, K.R. and Meller, R.D. (2009) Aisle configurations for unit-load warehouses. IIE Transactions 41 (3): 171–182.

    Google Scholar 

  • Günther, H.O. and Kim, K.H. (2005) Container Terminals and Automated Transport Systems Logistics Control Issues and Quantitative Decision Support. Berlin/Heidelberg, Germany: Springer.

    Google Scholar 

  • Guo, X.i. and Huang, S.Y. (2012) Dynamic space and time partitioning for yard crane workload management in container terminals. Transportation Science 46 (1): 134–148.

    Google Scholar 

  • Han, X.L., Lu, Z.Q. and Xi, L.F. (2010) A proactive approach for simultaneous berth and quay crane scheduling problem with stochastic arrival and handling time. European Journal of Operational Research 207 (3): 1327–1340.

    Google Scholar 

  • Hansen, P., Oguz, C. and Mladenovic, N. (2008) Variable neighborhood search for minimum cost berth allocation. European Journal of Operational Research 191 (3): 636–649.

    Google Scholar 

  • He, J., Chang, D., Mi, W. and Yan, W. (2010) A hybrid parallel genetic algorithm for yard crane scheduling. Transportation Research Part E: Logistics and Transportation Review 46 (1): 136–155.

    Google Scholar 

  • Heaver, T., Meersman, H. and Van de Voorde, E. (2001) Co-operation and competition in international container transport: Strategies for ports. Maritime Policy & Management 28 (3): 293–305.

    Google Scholar 

  • Heinrich, C. and Betts, B. (2003) Adapt or Die Transforming Your Supply Chain into an Adaptive Business Network. New Jersey: John Wiley & Sons.

    Google Scholar 

  • Hendriks, M., Laumanns, M., Lefeber, E. and Udding, J.T. (2010) Robust cyclic berth planning of container vessels. OR Spectrum 32 (3): 501–517.

    Google Scholar 

  • Hendriks, M.P.M., Armbruster, D., Laumanns, M., Lefeber, E. and Udding, J.T. (2012) Strategic allocation of cyclically calling vessels for multi-terminal container operators. Flexible Services and Manufacturing Journal 24 (3): 248–273.

    Google Scholar 

  • Hu, L., Shi, X., Voß, S. and Zhang, W. (2011) Application of RFID technology at the entrance gate of container terminals. In: J.W. Böse, H. Hu, C. Jahn, X. Shi, R. Stahlbock and S. Voß (eds.) Computational Logistics, Lecture Notes in Computer Science. Vol. 6971. Berlin/Heidelberg, Germany: Springer, pp. 209–220.

    Google Scholar 

  • Huang, S.H. and Lin, T.H. (2012) Heuristic algorithms for container pre-marshalling problems. Computers & Industrial Engineering 62 (1): 13–20.

    Google Scholar 

  • Huynh, N. and Walton, C.M. (2008) Robust scheduling of truck arrivals at marine container terminals. Journal of Transportation Engineering 134 (8): 347–353.

    Google Scholar 

  • Huynh, N. and Walton, C.M. (2011) Improving efficiency of drayage operations at seaport container terminals through the use of an appointment system. In: J.W. Böse, R. Sharda and S. Voß (eds.) Handbook of Terminal Planning, Operations Research/Computer Science Interfaces Series. Vol. 49. New York: Springer, pp. 323–344.

    Google Scholar 

  • Iannone, F. (2012) The private and social cost efficiency of port hinterland container distribution through a regional logistics system. Transportation Research Part A: Policy and Practice 46 (9): 1424–1448.

    Google Scholar 

  • Imai, A., Nishimura, E. and Papadimitriou, S. (2013) Marine container terminal configurations for efficient handling of mega-containerships. Transportation Research Part E: Logistics and Transportation Review 49 (37): 141–158.

    Google Scholar 

  • Jaehn, F. (2013) Positioning of loading units in a transshipment yard storage area. OR Spectrum 35 (2): 399–416.

    Google Scholar 

  • Jeon, S.M., Kim, K.H. and Kopfer, H. (2011) Routing automated guided vehicles in container terminals through the q-learning technique. Logistics Research 13 (1): 19–27.

    Google Scholar 

  • Jordan, M.A. (1997) Super Productive Cranes. Technical Report, Lifetech Consultants Inc. Jordan.

  • Jordan, M.A. (2002) Quay Crane Productivity. Technical Report, Lifetech Consultants Inc.

  • Kang, S., Medina, J.C. and Ouyang, Y. (2008) Optimal operations of transportation fleet for unloading activities at container ports. Transportation Research Part B: Methodological 42 (10): 970–984.

    Google Scholar 

  • Kemme, N. (2012) Effects of storage block layout and automated yard crane systems on the performance of seaport container terminals. OR Spectrum 34 (3): 563–591.

    Google Scholar 

  • Kim, K.H. and Kim, K.Y. (1999) An optimal routing algorithm for a transfer crane in port container terminals. Transportation Science 33 (1): 17–33.

    Google Scholar 

  • Kim, K.H. and Park, K.T. (2003) A note on a dynamic space-allocation method for outbound containers. European Journal of Operational Research 148 (1): 92–101.

    Google Scholar 

  • Kim, K., Park, Y.M. and Jin, M.J. (2008) An optimal layout of container yards. OR Spectrum 30 (4): 675–695.

    Google Scholar 

  • Kim, K.H., Park, Y.M. and Ryu, K.R. (2000) Deriving decision rules to locate export containers in container yards. European Journal of Operational Research 124 (1): 89–101.

    Google Scholar 

  • Kim, S. (2009) The toll plaza optimization problem: Design, operations, and strategies. Transportation Research Part E: Logistics and Transportation Review 45 (1): 125–137.

    Google Scholar 

  • Kosmatopoulos, E.B., Liu, Q. and Ioannou, P. (2002) Design and Optimization of a Conceptual Automated Yard Using Overhead Grid Rail System. Los Angeles, CA: METRANS Transportation Center.

    Google Scholar 

  • Lang, N. and Veenstra, A. (2010) A quantitative analysis of container vessel arrival planning strategies. OR Spectrum 32 (3): 477–499.

    Google Scholar 

  • Leachman, R.C. and Jula, P. (2012) Estimating flow times for containerized imports from Asia to the United States through the western rail network. Transportation Research Part E: Logistics and Transportation Review 48 (1): 296–309.

    Google Scholar 

  • Lee, Y. and Chao, S.L. (2009) A neighborhood search heuristic for pre-marshalling export containers. European Journal of Operational Research 196 (2): 468–475.

    Google Scholar 

  • Lee, Y. and Hsu, N.Y. (2007) An optimization model for the container pre-marshalling problem. Computers & Operations Research 34 (11): 3295–3313.

    Google Scholar 

  • Lee, B.K. and Kim, K.H. (2010) Optimizing the block size in container yards. Transportation Research Part E 46 (1): 120–135.

    Google Scholar 

  • Lee, B.K. and Kim, K.H. (2013) Optimizing the yard layout in container terminals. OR Spectrum 35 (2): 363–398.

    Google Scholar 

  • Lee, D.H., Jin, J.G. and Chen, J.H. (2012) Terminal and yard allocation problem for a container transshipment hub with multiple terminals. Transportation Research Part E: Logistics and Transportation Review 48 (38): 516–528.

    Google Scholar 

  • Lee, Y. and Lee, Y.J. (2010) A heuristic for retrieving containers from a yard. Computers & Operations Research 37 (6): 1139–1147.

    Google Scholar 

  • Legato, P., Trunfio, R. and Meisel, F. (2012) Modeling and solving rich quay crane scheduling problems. Computers & Operations Research 39 (9): 2063–2078.

    Google Scholar 

  • Li, W., Goh, M., Wu, Y., Petering, M.E.H., De Souza, R. and Wu, Y.C. (2012) A continuous time model for multiple yard crane scheduling with last minute job arrivals. International Journal of Production Economics 136 (2): 332–343.

    Google Scholar 

  • Li, W., Wu, Y., Petering, M.E.H., Goh, M. and de Souza, R. (2009) Discrete time model and algorithms for container yard crane scheduling. European Journal of Operational Research 198 (1): 165–172.

    Google Scholar 

  • Lim, A., Rodrigues, B. and Zhou, X. (2007) A m-parallel crane scheduling problem with a non-crossing constraint. Naval Research Logistics 54 (2): 115–127.

    Google Scholar 

  • Lu, Z., Han, X., Xi, L. and Erera, A.L. (2012) A heuristic for the quay crane scheduling problem based on contiguous bay crane operations. Computers & Operations Research 39 (12): 2915–2928.

    Google Scholar 

  • Maersk Line. (2011) Maersk line orders 10 ‘triple-e’ mega-ships. http://www.maerskline.com/link/?page=news&path=/news/story_page/11/Triple_E, accessed 1 August 2013.

  • Meisel, F. (2009) Seaside Operations Planning in Container Terminals. Heidelberg, Germany: Physica Verlag.

    Google Scholar 

  • Meisel, F. and Bierwirth, C. (2011) A unified approach for the evaluation of quay crane scheduling models and algorithms. Computers & Operations Research 38 (3): 683–693.

    Google Scholar 

  • Meisel, F. and Wichmann, M. (2010) Container sequencing for quay cranes with internal reshuffles. OR Spectrum 32 (3): 569–591.

    Google Scholar 

  • Mes, M.R.K. (2012) http://bat-man.nl/documentatie.php, accessed 23 November 2012.

  • Midoro, R., Musso, E. and Parola, F. (2005) Maritime liner shipping and the stevedoring industry: Market structure and competition strategies. Maritime Policy & Management 32 (2): 89–106.

    Google Scholar 

  • Murty, K.G., Liu, J., Wan, Y.W. and Linn, R. (2005) A decision support system for operations in a container terminal. Decision Support Systems 39 (3): 309–332.

    Google Scholar 

  • Namboothiri, R. and Erera, A.L. (2008) Planning local container drayage operations given a port access appointment system. Transportation Research Part E: Logistics and Transportation Review 44 (2): 185–202.

    Google Scholar 

  • Narasimhan, A. and Palekar, U.S. (2002) Analysis and algorithms for the transtainer routing problem in container port operations. Transportation Science 36 (1): 63–78.

    Google Scholar 

  • NauticExpo. (2012) http://www.nauticexpo.com/prod/liebherr-international-deutschland/container-stacking-cranes-rubber-tired-30468-189567.html, accessed 4 April 2012.

  • Newman, A.M. and Yano, C.A. (2000) Scheduling direct and indirect trains and containers in an intermodal setting. Transportation Science 34 (3): 256–270.

    Google Scholar 

  • Ng, W.C. (2005) Crane scheduling in container yards with inter-crane interference. European Journal of Operational Research 164 (1): 64–78.

    Google Scholar 

  • Ngai, E.W.T. et al (2011) Design and development of an intelligent context-aware decision support system for real-time monitoring of container terminal operations. International Journal of Production Research 49 (12): 3501–3526.

    Google Scholar 

  • Nguyen, V.D. and Kim, K.H. (2009) A dispatching method for automated lifting vehicles in automated port container terminals. Computers & Industrial Engineering 56 (3): 1002–1020.

    Google Scholar 

  • Notteboom, T.E. (2002) Consolidation and contestability in the European container handling industry. Maritime Policy & Management 29 (3): 257–269.

    Google Scholar 

  • Notteboom, T.E. and Winkelmans, W. (2001) Structural changes in logistics: How will port authorities face the challenge? Maritime Policy & Management 28 (1): 71–89.

    Google Scholar 

  • Ottjes, J.A., Veeke, H.P.M., Duinkerken, M.B., Rijsenbrij, J.C. and Lodewijks, G. (2007) Simulation of a multiterminal system for container handling. In: K.H. Kim and H.O. Günther (eds.) Container Terminals and Cargo Systems. Berlin/Heidelberg, Germany: Springer, pp. 15–36.

    Google Scholar 

  • Öztürkoģlu, Ö., Gue, K.R. and Meller, R.D. (2012) Optimal unit-load warehouse designs for single command operations. IIE Transactions 44 (6): 459–475.

    Google Scholar 

  • Park, T., Choe, R., Ok, S.M. and Ryu, K.R. (2010) Real-time scheduling for twin rmgs in an automated container yard. OR Spectrum 32 (3): 593–615.

    Google Scholar 

  • Petering, M.E.H. (2010) Development and simulation analysis of real-time, dual-load yard truck control systems for seaport container transshipment terminals. OR Spectrum 32 (3): 633–661.

    Google Scholar 

  • Petering, M.E.H. (2011) Decision support for yard capacity, fleet composition, truck substitutability, and scalability issues at seaport container terminals. Transportation Research Part E: Logistics and Transportation Review 47 (1): 85–103.

    Google Scholar 

  • Petering, M.E.H. and Murty, K.G. (2009) Effect of block length and yard crane deployment systems on overall performance at a seaport container transshipment terminal. Computers & Operations Research 36 (5): 1711–1725.

    Google Scholar 

  • Petering, M.E.H., Wu, Y., Li, W., Goh, M. and de Souza, R. (2009) Development and simulation analysis of real-time yard crane control systems for seaport container transshipment terminals. OR Spectrum 31 (4): 801–835.

    Google Scholar 

  • Port of Rotterdam Authority. (ed.) (2012) Port Vision 2030: Port Compass. Rotterdam, the Netherlands: Port of Rotterdam Authority.

  • Port of Rotterdam Authority. (ed.) (2014) Abridged Annual Report 2013, Port of Rotterdam Authority, Rotterdam.

  • Robinson, R. (2002) Ports as elements in value-driven chain systems: The new paradigm. Maritime Policy & Management 29 (3): 241–255.

    Google Scholar 

  • Roso, V., Woxenius, J. and Lumsden, K. (2009) The dry port concept: Connecting container seaports with the hinterland. Journal of Transport Geography 17 (5): 338–345.

    Google Scholar 

  • Roy, D., Gupta, A., Parhi, S. and de Koster, M.B.M. (2014) Optimal stack layout in a sea container terminal with automated lifting vehicles. ERIM Report Series Reference No. ERS-2014-012-LIS, http://ssrn.com/abstract=2491023.

  • Saurì, S. and Martin, E. (2011) Space allocating strategies for improving import yard performance at marine terminals. Transportation Research Part E: Logistics and Transportation Review 47 (6): 1038–1057.

    Google Scholar 

  • Shanghai International Port (Group) Co. Ltd. (2014) News room. http://www.portshanghai.com.cn, accessed 12 February 2015.

  • Sharif, O. and Huynh, N. (2012) Yard crane scheduling at container terminals: A comparative study of centralized and decentralized approaches. Maritime & Economics Logistics 14 (2): 139–161.

    Google Scholar 

  • Sharypova, K., Crainic, T.G., van Woensel, T. and Fransoo, J.C. (2012) Scheduled Service Network de Sign with Synchronization and Transshipment Constraints for Intermodal Container Transportation Networks. Working Paper, TU Eindhoven.

  • Stahlbock, R. and Voß, S. (2008a) Operations research at container terminals: A literature update. OR Spectrum 30 (1): 1–52.

    Google Scholar 

  • Stahlbock, R. and Voß, S. (2008b) Vehicle routing problems and container terminal operations an update of research. The Vehicle Routing Problem: Latest Advances And New Challenges 43 (3): 551–589.

    Google Scholar 

  • Stahlbock, R. and Voß, S. (2010) Efficiency considerations for sequencing and scheduling of double-rail mounted gantry cranes at maritime container terminals. International Journal of Shipping and Transport Logistics 2 (1): 95–123.

    Google Scholar 

  • Steenken, D., Voß, S. and Stahlbock, R. (2004) Container terminal operation and operations research a classification and literature review. OR Spectrum 26 (1): 3–49.

    Google Scholar 

  • Taggart, S. (1999) The 20-ton packet. Wired Magazine 7(10) 246. TBA BV. (2012). http://www.tba.nl/index.php?mid=21&lang=en, accessed 5 December 2012.

  • Tierney, K., Voß, S. and Stahlbock, R. (2013) A Mathematical Model of Inter-Terminal Transportation. Technical Report, IT University of Copenhagen, Rotterdam.

  • Ting, S.L., Wang, L.X. and Ip, W.H. (2012) A study of RFID adoption for vehicle tracking in a container terminal. Journal of Industrial Engineering and Management 5 (1): 22–52.

    Google Scholar 

  • United Nations: ESCAP. (2007) Regional Shipping and Port Development: Container Traffic Forecast 2007 Update. New York: United Nations: Economic and Social Commission for Asia and the Pacific (ESCAP).

  • US Customs and Border Protection, Washington, D.C., USA. (2011) Container security initiative: Just the facts. from http://www.porttechnology.org/images/uploads/technical_papers/PT37-08.pdf, accessed 12 February 2015.

  • Van Asperen, E., Borgman, B. and Dekker, R. (2011) Evaluating impact of truck announcements on container stacking efficiency. Flexible Services and Manufacturing Journal 25 (4): 543–556.

    Google Scholar 

  • Van Klink, H.A. and Van den Berg, G.C. (1998) Gateways and intermodalism. Journal of Transport Geography 6 (1): 1–9.

    Google Scholar 

  • Van Riessen, B., Negenborn, R.R., Dekker, R. and Lodewijks, G. (2013) Service Network Design for An Intermodal Container Network with Flexible Due Dates/Times and the Possibility of Using Sub Contracted Transport. Econometric Institute Report, Erasmus University Rotterdam (2013-17): 1–16.

  • Veenstra, A., Zuidwijk, R. and Van Asperen, E. (2012) The extended gate concept for container terminals: Expanding the notion of dry ports. Maritime Economics & Logistics 14 (1): 14–32.

    Google Scholar 

  • Vervest, P. and Li, Z. (2009) The Network Experience New Value From Smart Business Networks. Berlin, Germany: Springer.

    Google Scholar 

  • Vidal, J.M. and Huynh, N. (2010) Building Agent-Based Models of Seaport Container Terminals, José M. Vidal and Nathan Huynh, Proc. of 6th Workshop on Agents in Traffic and Transportation, Kluegl, Ossowski, Chaib-Draa and Bazzan (eds.), May, 11, 2010, Toronto, Canada.

  • Vis, I.F.A. and Carlo, H.J. (2010) Sequencing two cooperating automated stacking cranes in a container terminal. Transportation Science 44 (2): 169–182.

    Google Scholar 

  • Vis, I.F.A. and De Koster, R. (2003) Transshipment of containers at a container terminal: An overview. European Journal of Operational Research 147 (1): 1–16.

    Google Scholar 

  • Vis, I.F.A. and Roodbergen, K.J. (2009) Scheduling of container storage and retrieval. Operations Research 57 (2): 456–467.

    Google Scholar 

  • Vis, I.F.A. (2006) A comparative analysis of storage and retrieval equipment at a container terminal. International Journal of Production Economics 103 (2): 680–693.

    Google Scholar 

  • Vis, I. and Van Anholt, R. (2010) Performance analysis of berth configurations at container terminals. OR Spectrum 32 (3): 453–476.

    Google Scholar 

  • Wang, F. and Lim, A. (2007) A stochastic beam search for the berth allocation problem. Decision Support Systems 42 (4): 2186–2196.

    Google Scholar 

  • Wang, W.F. and Yun, W.Y. (2013) Scheduling for inland container truck and train transportation. International Journal of Production Economics 143 (2): 349–356.

    Google Scholar 

  • Wiegmans, B.W., Ubbels, B., Rietveld, P. and Nijkamp, P. (2002) Investments in container terminals: Public private partnerships in Europe. International Journal of Maritime Economics 4 (1): 1–20.

    Google Scholar 

  • Wiese, J., Suhl, L. and Kliewer, N. (2010) Mathematical models and solution methods for optimal container terminal yard layouts. OR Spectrum 32 (3): 427–452.

    Google Scholar 

  • Wiese, J., Suhl, L. and Kliewer, N. (2011) An analytical model for designing yard layouts of a straddle carrier based container terminal. Flexible Services and Manufacturing Journal 25 (4): 466–502.

    Google Scholar 

  • Wilson, I.D. and Roach, P.A. (2000) Container stowage planning: A methodology for generating computerised solutions. Journal of Operational Research Society 51 (11): 1248–1255.

    Google Scholar 

  • Woxenius, J. and Bergqvist, R. (2011) Comparing maritime containers and semi-trailers in the context of hinterland transport by rail. Journal of Transport Geography 19 (4): 680–688.

    Google Scholar 

  • Xing, Y., Yin, K., Quadrifoglio, L. and Wang, B. (2012) Dispatch problem of automated guided vehicles for serving tandem lift quay crane, transportation research record. Journal of the Transportation Research Board 2273 (1): 79–86.

  • Xu, D., Li, C.L. and Leung, J.Y.T. (2012) Berth allocation with time-dependent physical limitations on vessels. European Journal of Operational Research 216 (1): 47–56.

    Google Scholar 

  • Yano, C.A. and Newman, A.M. (2001) Scheduling trains and containers with due dates and dynamic arrivals. Transportation Science 35 (2): 181–191.

    Google Scholar 

  • Young, B. (2012) Amsterdam’s white elephant is put out of its misery. http://theloadstar.co.uk/amsterdams-white-elephant-is-put-out-of-its-misery/, accessed 4 April 2012.

  • Ypsilantis, P. and Zuidwijk, R.A. (2013) Joint Design and Pricing of Intermodal Port Hinterland Network Services: Considering Economies of Scale and Service Time Constraints. Working Paper, Erasmus University Rotterdam.

  • Yu, M. and Qi, X. (2013) Storage space allocation models for inbound containers in an automatic container terminal. European Journal of Operational Research 226 (1): 32–45.

    Google Scholar 

  • Zhang, C., Chen, W., Shi, L. and Zheng, L. (2010) A note on deriving decision rules to locate export containers in container yards. European Journal of Operational Research 205 (2): 483–485.

    Google Scholar 

  • Zhang, C., Wan, Y.W., Liu, J. and Linn, R.J. (2002) Dynamic crane deployment in container storage yards. Transportation Research Part B: Methodological 36 (6): 537–555.

    Google Scholar 

  • Zhao, W. and Goodchild, A.V. (2010) The impact of truck arrival information on container terminal rehandling. Transportation Research Part E: Logistics and Transportation Review 46 (3): 327–343.

    Google Scholar 

  • Zhu, M., Fan, X., Cheng, H. and He, Q. (2010) Modeling and simulation of automated container terminal operation. Journal of Computers 5 (6): 951–957.

    Google Scholar 

Download references

Acknowledgements

We would like to thank the reviewers for their suggestions, which greatly improved the quality of this article and SmartPort Research Centre at Erasmus University (www.eur.nl/smartport) for funding this research.

Author information

Authors and Affiliations

Authors

Rights and permissions

Reprints and permissions

About this article

Check for updates. Verify currency and authenticity via CrossMark

Cite this article

Gharehgozli, A., Roy, D. & de Koster, R. Sea container terminals: New technologies and OR models. Marit Econ Logist 18, 103–140 (2016). https://doi.org/10.1057/mel.2015.3

Download citation

  • Published:

  • Issue Date:

  • DOI: https://doi.org/10.1057/mel.2015.3

Keywords

Navigation