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Presentation at Graduate Student Day, 2012 Inter-Block Yard Crane Scheduling a t a Marine Container Terminal by Omor Sharif, Nathan Huynh, Mashrur Chowdhury , Jose Vidal Paper submitted to International Journal of Transportation Science and Technology.

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slide1

Presentation at Graduate Student Day, 2012

Inter-Block Yard Crane Scheduling

at a Marine Container Terminal

by

Omor Sharif, Nathan Huynh, MashrurChowdhury, Jose Vidal

Paper submitted to

International Journal of Transportation Science and Technology

a very brief review of a container terminal
A Very Brief Review of A Container Terminal!
  • An interface between ocean and land transport
  • Containers are loaded/unloaded to/from a ship
  • Operation involves a large number of decisions
  • Capacity Constraints, Environmental Concerns etc
research problem and motivation
Research problem and Motivation
  • Container Yard and Yard Crane (YC)
  • A container yard is made up of several blocks of containers
  • Workload varies among blocks during operational hours
  • Efficiency of YCs impacts truck waiting/ship waiting time
  • Assign/relocate YCs among blocks to finish most work
  • Known as Interblock YC Scheduling Problem
model assumptions
Model Assumptions
  • Total operational hours is divided in several planning periods
  • A workload forecast for blocks is known at start (time-units)
  • At most two cranes work at a block at the same time
  • At most one transfer per planning period
  • Other operations will not introduce delay
  • 10 minutes transfer time for each longitudinal block traveled
an algorithm to assign cranes to blocks
An algorithm to assign cranes to blocks
  • 1. Each crane j proposes to first block i from its preference list
  • 2. Each block i receiving more than qi proposals, ‘holds’ the most preferred qi cranes and rejects all others.
  • n. Each crane j rejected at step n − 1 removes the block i rejecting the crane from its preference list.
  • Then the rejected crane j makes a new proposal to its next most preferred block i who hasn’t yet rejected it.
  • Go to step n − 1.
implementation
Implementation
  • Multi-agent simulation GUI
  • Implemented in NETLOGO
  • Stationary block and Mobile crane agents
results contd percentage incomplete work volume case ii average number of cranes per block 1 5
Results (Contd..)Percentage incomplete work volume: Case II - average number of cranes per block = 1.5
concluding remarks

Summary of Findings

  • Future Work
Concluding remarks
  • In ‘medium’ condition all work can be finished
  • In ‘heavy’ condition the percentage incomplete is 1% or less
  • In ‘above capacity’ condition the percentage remaining is within 3% of the lower bound.
  • Scalable; a test case with 30 blocks can be solved within 3 seconds
  • Consider relocating cranes multiple time
  • Include forecasts for multiple planning periods
  • Solve integrated problems involving other related decisions
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