Article | 30th Annual Workshop of the Swedish Artificial Intelligence Society SAIS 2017, May 15–16, 2017, Karlskrona, Sweden | Improved Inter Terminal Transportation using Agent Technology
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Title:
Improved Inter Terminal Transportation using Agent Technology
Author:
Lawrence Henesey: Blekinge Tekniska Högskola, Blekinge Institute of Technology, Karlshamn, Sweden
Download:
Full text (pdf)
Year:
2017
Conference:
30th Annual Workshop of the Swedish Artificial Intelligence Society SAIS 2017, May 15–16, 2017, Karlskrona, Sweden
Issue:
137
Article no.:
007
Pages:
60-67
No. of pages:
8
Publication type:
Abstract and Fulltext
Published:
2017-05-12
ISBN:
978-91-7685-496-9
Series:
Linköping Electronic Conference Proceedings
ISSN (print):
1650-3686
ISSN (online):
1650-3740
Publisher:
Linköping University Electronic Press, Linköpings universitet


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Many maritime logistics centres worldwide are experiencing large number of inter-terminal transportation volumes, which raises the complexity of transportation processes between the terminals. Different vehicle systems exist for transporting containers between different terminals, however they often are inefficient due to poor planning or scheduling. We present a solution for dynamic planning of resources by using an agent based simulation tool. The results showed improved resource planning and utilization of different resources in the network of terminals. A cost comparison of different vehicles systems is further analysed in order to identify the best choice of vehicle system for a given scenario.

Keywords: Inter-terminal transportation, Container terminal, Automated guided vehicle, Agent based simulation

30th Annual Workshop of the Swedish Artificial Intelligence Society SAIS 2017, May 15–16, 2017, Karlskrona, Sweden

Author:
Lawrence Henesey
Title:
Improved Inter Terminal Transportation using Agent Technology
References:

[1] Duinkerken, M. B., Dekker, R., Kurstjens, S. T. G. L., Ottjes, J. A., & Dellaert, N. P. 2007. Comparing transportation systems for inter-terminal transport at the Maasvlakte container terminals. In P. K. H. Kim & P. D. H.-O. Günther (Eds.), Container Terminals and Cargo Systems (pp. 37–61).


[2] Douma, A. M. 2008. Aligning the operations of barges and terminals through distributed planning. University of Twente.


[3] Douma, A. M., Schuur, P. C., & Schutten, J. M. J. 2011. Aligning barge and terminal operations using service-time profiles. Flexible Services and Manufacturing Journal, 23(4), 385–421.


[4] Douma, A., Schutten, M., & 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.


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


[6] Drewry. 2012. Container terminal capacity and performance benchmarks. London: Drewry Shipping Consultants Ltd ~ The Independent Maritime Adviser.


[7] Ottjes, J. A., Veeke, H. P. M., Duinkerken, M. B., Rijsenbrij, J. C., & Lodewijks, G. 2007. Simulation of a multiterminal system for container handling. In P. K. H. Kim & P. D. H.-O. Günther (Eds.), Container Terminals and Cargo Systems (pp. 15–36). Springer Berlin Heidelberg.


[8] Peng, Y., & Junqing, S. 2009. Agent Based Container Terminal Optimization. In IITA International Conference on Control, Automation and Systems Engineering, 2009. CASE 2009 (pp. 607–609).


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


[10] Stahlbock, R., & Voß, S. 2008. Operations research at container terminals: a literature update. OR Spectrum, 30(1), 1–52.


[11] Ng, W. C., & Mak, K. L. 2005. Yard crane scheduling in port container terminals. Applied Mathematical Modelling, 29(3), 263–276.


[12] Kap Hwan Kim. 1997. Evaluation of the number of rehandles in container yards. Computers & Industrial Engineering, 32(4), 701–711.


[13] Ambrosino, D., Bramardi, A., Pucciano, M., Sacone, S., & Siri, S. 2011. Modelling and solving the train load planning problem in seaport container terminals. In 2011 IEEE Conference on Automation Science and Engineering (CASE) (pp. 208–213). K


[14] Kim, K. H., & Moon, K. C. 2003. Berth scheduling by simulated annealing. Transportation Research Part B: Methodological, 37(6), 541–560. [


[15] Henesey, L., Davidsson, P., & Persson, J. A. 2009. Agent based simulation architecture for evaluating operational policies in transshipping containers. Autonomous Agents and Multi-Agent Systems.


[16] Huynh, J. M. V. and N. 2010. Building Agent-Based Models of Seaport Container Terminals [text]. Retrieved April 5, 2017 from http://jmvida.cse.sc.edu/lib/vidal10a.html


[17] Kulaka, O., Polata, O., & Guenther, H.-O. 2008. Performance evaluation of container terminal operations. IT Based Planning and Control of Seaport Container Terminals and Transport Systems. [18] Li, B., & Li, W. 2010. Modelling and simulation of container terminal logistics systems using Harvard architecture and agent-based computing. In Simulation Conference (WSC), Proceedings of the 2010 Winter (pp. 3396–3410).


[19] Liu, C. I., Jula, H., & Ioannou, P. A. 2001. A simulation approach for performance evaluation of proposed automated container terminals. In 2001 IEEE Intelligent Transportation Systems, 2001. Proceedings (pp. 563–568).


[20] Ottjes, J. A., Duinkerken, M. B., Evers, J. J. M., & Dekker, R. 1996. Robotised Inter Terminal Transport of Containers. In Proceedings 8th European Simulation Symposium. Genua [SCS (pp. 621–625).


[21] Yun, W. Y., & Choi, Y. S. 1999. A simulation model for container-terminal operation analysis using an object-oriented approach. International Journal of Production Economics, 59(1–3), 221–230.


[22] Henesey, L. E. 2006. Multi-Agent Systems for Container Terminal Management. Blekinge Institute of Technology. PhD Thesis.


[23] Hoshino, S., Ota, J., Shinozaki, A. ., & Hashimoto, H. . 2005. Highly efficient AGV transportation system management using agent cooperation and container storage planning. In 2005 IEEE/RSJ International Conference on Intelligent Robots and Systems, 2005.


[24] Henesey, L. E., Notteboom, T. E., & Davidsson, P. 2003. Agent-based simulation of stakeholders relations: An approach to sustainable port and terminal management. In International Association of Maritime Economists Annual Conference, 2003 pp. 314–331.


[25] Rebollo, M., Julian, V., Carrascosa, C., & Botti, V. 2000. A Multi-Agent System for the Automation of a Port Container Terminal. Autonomous Agents 2000 workshop on Agents in Industry.


[26] Van Dam, K. H., Verwater-Lukszo, Z., Ottjes, J. A., & Lodewijks, G. 2006. Distributed intelligence in autonomous multi-vehicle systems. International Journal of Critical Infrastructures, 2(2), 261–272.


[27] Henesey, L., Davidsson, P., & Persson, J. A. 2009. Agent based simulation architecture for evaluating operational policies in transshipping containers. Autonomous Agents and Multi-Agent Systems, 18(2), 220–238.


[28] Duinkerken, I. M. B., Ottjes, J. A., Evers, J. J. M., Kurstjens, S. T. G. L., Dekker, R., Dellaert, N. P., Cpim, D. 1996. Simulation Studies on Inter Terminal Transport at the Maasvlakte. In Simulation Studies on Inter Terminal Transport at the Maasvlakte. In Proceeding of 2nd Trail PhD Congress 1996 “Defense or attack”. May 1996. Rotterdam (TRAIL). ISBN 90-5584-020-3.


[29] Sterzik, S., & Kopfer, H. 2013. A Tabu Search Heuristic for the Inland Container Transportation Problem. Computers & Operations Research, 40(4), 953–962.


[30] Tierney, K., Voß, S., & Stahlbock, R. 2014. A mathematical model of inter-terminal transportation. European Journal of Operational Research, 235(2), 448–460.


[31] Wooldridge, M., & Jennings, N. R. 1995. Intelligent Agents: Theory and Practice. Knowledge Engineering Review, 10, 115–152.


[32] Durfee, E. H., & Lesser, V. R. 1989. Negotiating task decomposition and allocation using partial global planning. In M. Huhns (Ed.), Distributed Artificial Intelligence (Vol. 2, pp. 229–243). San Francisco, CA, USA: Morgan Kaufmann Publishers Inc.


[33] Sha, M. 2008. A simulation model for intra-terminal transport of Container Terminal operations system. In IEEE International Conference on Service Operations and Logistics, and Informatics, 2008. IEEE/SOLI 2008. Vol. 2, pp. 2810–2814.


[34] Sharif, O., & Huynh, N. 2013. Storage space allocation at marine container terminals using antbased control. Expert Systems with Applications, 40(6), 2323–2330.


[35] Shen, W., & Norrie, D. H. 1999. Agent-Based Systems for Intelligent Manufacturing: A State-of-the-Art Survey. Knowledge and Information Systems, 1(2), 129–156.


[36] Zhou, Z., Chan, W. K. (Victor), & Chow, J. H. 2009. Agent-based simulation of electricity markets: a survey of tools. Artificial Intelligence Review, 28(4), 305–342.


[37] StarLogo. (2006). Retrieved January 9, 2015, from http://education.mit.edu/starlogo/

30th Annual Workshop of the Swedish Artificial Intelligence Society SAIS 2017, May 15–16, 2017, Karlskrona, Sweden

Author:
Lawrence Henesey
Title:
Improved Inter Terminal Transportation using Agent Technology
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Last updated: 2017-02-21