Load Planning Optimization for Mega-Containerships

To enhance the competitiveness and efficiency of container terminals, reducing the berthing time of containerships plays an important role. The berthing time of a containership is mainly composed of the unloading and loading time of containers, which is affected by the horizontal distribution of containers over the bays. So to increase the terminal productivity and reduce the berthing time, the stowage planning must conform to the berth design. Since containers are handled from or to containerships by quay cranes, crane utilization also affects the berthing time. Given the configuration of berths and quay cranes at each visiting port, the stowage planning must consider the utilization of quay cranes as well as the reduction of unnecessary shifts to minimize the total berthing time at all ports over the voyage. So an optimization model is proposed to solve the integrated problem of stowage planning and crane split, which covers a wide range of operational and structural constraints. A meta-heuristic approach based on genetic algorithms with a novel encoding method is designed and implemented to solve real-size problems. The genetic encoding is ultra-compact and represents grouping, sorting and assignment strategies that might be applied to form the stowage pattern. The evaluation procedure accounts for technical specification of the cranes as well as the crane split. Numerical results show that timely solution for ultra large size containerships can be obtained under different scenarios.

  • Supplemental Notes:
    • This paper was sponsored by TRB committee AW010 Standing Committee on Ports and Channels.
  • Corporate Authors:

    Transportation Research Board

    ,    
  • Authors:
    • Hamedi, Masoud
    • Haghani, Ali
  • Conference:
  • Date: 2019

Language

  • English

Media Info

  • Media Type: Digital/other
  • Features: Figures; References; Tables;
  • Pagination: 21p

Subject/Index Terms

Filing Info

  • Accession Number: 01697478
  • Record Type: Publication
  • Report/Paper Numbers: 19-04742
  • Files: TRIS, TRB, ATRI
  • Created Date: Dec 7 2018 9:29AM