Group-bay stowage planning problem for container ship

• Autorzy: Shen Y. , Zhao N. , Mi W.
• Języki publikacji: EN

Abstrakty

EN

Stowage planning is the core of ship planning. It directly influences the seaworthiness of container ship and the handling efficiency of container terminal. As the latter step of container ship stowage plan, terminal stowage planning optimizes terminal cost according to pre-plan. Group-Bay stowage planning is the smallest sub problem of terminal stowage planning problem. A group-bay stowage planning model is formulated to minimize relocation, crane movement and target weight gap satisfying both ship owner and container terminal. A GA-A* hybrid algorithm is designed to solve this problem. Numerical experiment shown the validity and the efficiency

• Wydawca: -
• Czasopismo: Polish Maritime Research
• Rocznik: 2016
• Tom: 23
• Numer: Special Issue S1
• Opis fizyczny: p.152-159,fig.,ref.

Twórcy

autor

Shen Y.

• Scientific Research Academy, Shanghai Maritime University, 201306, Shanghai, China

autor

Zhao N.

• Logistics Engineering College, Shanghai Maritime University, 201306, Shanghai, China

autor

Mi W.

• Logistics Engineering College, Shanghai Maritime University, 201306, Shanghai, China

Bibliografia

• 1. Steenken, D., Voß, S., & Stahlbock, R. Container terminal operation and operations research A classification and literature review. OR Spectrum, 26(1), 2004, 3–49.
• 2. Alvarez, J. Ambrosino, D., Anghinolfi, D., Paolucci, M A heuristic for vessel planning in a reach stacker terminal[J]. Journal of Maritime Research, III(1), 2006, 3–16.
• 3. Mi Chao, Zhang Zhiwei, Huang Youfang, Shen Yang, A FAST AUTOMATED VISION SYSTEM FOR CONTAINER CORNER CASTING RECOGNITION,Journal of Marine Science and Technology-Taiwan, 2016, 24(1): 54-60. DOI: 10.6119/JMST-016-0125-8
• 4. Mi Chao, Shen Yang, Mi Weijian, Huang Youfang, Ship Identification Algorithm Based on 3D Point Cloud for Automated Ship Loaders, Journal of Coastal Research, 2015, 2015(SI.73):28-34. DOI: 10.2112/SI73-006.15. Wang Hongpeng. Knowledge-based Container Ship Automatic Stowage Expert System [J]. Journal of Shanghai Maritime University,2002,23(1):46-49.
• 6. Kang, J.-G., & Kim, Y.-D. Stowage planning in maritime container transportation[J]. Journal of the Operational Research Society, 53(4), 2002, 415–426.
• 7. Kim, K. H., Kang, J. S., & Ryu, K. R. A beam search algorithm for the load sequencing of outbound containers in port container terminals[J]. OR Spectrum, 26(1), 2004, 93–116.
• 8. Ambrosino D., Sciomachen A.. A constraints satisfaction approach for master bay plans[J]. In: Sciutto, G., Brebbia, C. (Eds.), Maritime Engineering and Ports. WIT Press, Boston, 1998, pp: 155–164.
• 9. Mi Chao, Zhang Zhiwei, He Xin, Huang Youfang, Mi Weijian, Two-stage classification approach for human detection in camera video in bulk ports,Polish Maritime Research, 2015, 22(SI.1):163-170. DOI: 10.1515/ pomr-2015-0049
• 10. Mi Chao, He Xin, Liu Haiwei, Huang Youfang, Mi Weijian, Research on a Fast Human-Detection Algorithm for Unmanned Surveillance Area in Bulk Ports,Mathematical Problems in Engineering, 2014, Article No.386764.DOI: 10.1155/2014/386764
• 11. Mi Chao, Liu Haiwei, Huang Youfang, Mi Weijian, Shen Yang, Fatigue alarm systems for port machine operators, ASIA LIFE SCIENCES, 2016,25(1):31-41.
• 12. Winter T.. Online and Real-Time Dispatching Problems[D], PhD thesis, Technical University of Braunschweig, Germany, 1999.
• 13. Cho D.W.. Development of a methodology for containership load planning[D], PhD thesis, Oregon State University, 1984.
• 14. Botter R.C., Brinati M.A.. Stowage container planning: a model for getting an poptimal solution[J],IFIP Trans. B (App. in Tech.), 1992, B-5: 217–229.
• 15. Avriel M., Penn M.. Exact and approximate solutions of the container ship stowage problem[J]. Computers & Industrial Engineering, 1993, 25: 271–274.
• 16. Avriel M., Penn M., Shpirer N., Witteboon S.. Stowage planning for container ships to reduce the number of shifts[J]. Annals of Operations Research, 1998, 76: 55–71.
• 17. Ambrosino D., Sciomachen A.,Tanfani E.. Stowing a containership: the master bay plan problem[J]. Transportation Research A, 2004, 38(2): 81-99.
• 18. Sciomachen A., Tanfani E.. A 3D-BPP approach for optimising stowage plans and terminal productivity[J]. European Journal of Operational Research, 2007, 183: 1433–1446.
• 19. Pacino, D., Delgado, A., Jensen, R. M., & Bebbington, T. Fast generation of near-optimal plans for eco-efficient stowage of large container vessels. In Proceedings of the second international conference on computational logistics, 2011, ICCL’11 (pp. 286–301), Berlin, Heidelberg: Springer-Verlag.
• 20. Delgado, A., Jensen, R. M., Janstrup, K., Rose, T. H., & Andersen, K. H. A constraint programming model for fast optimal stowage of container vessel bays. European Journal of Operational Research, 2012, 220, 251–261.

Identyfikatory

DOI

10.1515/pomr-2016-0060