Abstract

The operational efficiency of a port depends on proper container movement planning, called “stowage planning”, especially because unloading and loading container ships demands time, and this has a cost. Thus, the optimization of operations through stages is important to avoid blockage activities. This paper proposes a framework for solving the 3D stowage planning (3D SP) problem for container ships integrated with the scheduling of quay cranes (SQC) problem. 3D SP and SQC problems are interrelated and combinatorial, justifying the applications of meta-heuristics like a genetic algorithm combined with simulation and representation by rules. The robustness of the developed approach is attested in problems with 30 ports, 1500 TEUs ship or 15 ports and 22,000 TEUs ship and two quay cranes. These studies showed that the addition of the SQC problem leads to a 45.82% increase in load/unload time for the 3D SP problem solution, on average. This could help the charterer to avoid paying charges to the shipowner due to its an extra unplanned use of the vessel. Additionally, the developed methodology also helps to explain a long term phenomena of continuous increasing in container ship capacity since 1950s.

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