Container-ships are vessels possessing an internal structure that facilitates the handling of containerised cargo. At each port along the vessel’s journey, containers destined for that port are unloaded, and additional containers destined for subsequent ports are loaded. Determining a viable configuration of containers that facilitates this process, in a cost-effective way, constitutes the deep-sea container-ship stowage problem. The work of determining a stowage configuration for a container-ship, on leaving a port, is performed by human stowage planners, who work under strict time constraints, and are limited in the number of configurations that they can consider. Little work has been published in the area of full automation of stowage planning. Authors proposing full automation have correctly identified the salient features of the problem, but have failed to recognize how human planners solve the problem, instead allowing the array-like nature of spaces within containerised vessels to entirely dictate their approach to a solution. To enable implementation of these approaches, excessively large search spaces are pruned through the removal of important features of the problem, rendering the solutions not commercially viable. This paper proposes an approach which can determine good sub-optimal solutions to the entire problem in a commercially viable duration of time. This is achieved through an intelligent analysis of the domain allowing the problem to be divided into sub-problems, each of which may be solved through the application of search. Further, this approach allows many more stowage configurations to be considered than would be possible for a human planner.
|Number of pages||7|
|Publication status||Published - 1997|