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Automatic layout of variable-content print data
Keyword(s): print layout; paste-up; floorplanning; genetic algorithm; self-organising documents; BICAS
Abstract: The increasing quantity of data held by organisations about individuals, and the recent development of digital press capable of one-off printing at a quality rivalling offset machines, have created a demand for a method to automatically generate page layouts. The present solutions to this are either to use skilled labour to hand-design each page, or constrain the design tightly by fitting everything to a template, both of which have significant drawbacks. This thesis describes a Genetic Algorithm (GA) that automatically generates page layouts, without the need for costly and time-consuming human design, and with considerably more flexibility than a template-based approach. The GA is based on related work in VLSI floorplanning, which is described and adapted for the print context. This method was found to produce attractive layouts with a relatively small number of iterations, even though the only explicit goal in the program was to minimise wasted space. Visual representations of the layout are presented and discussed, together with an analysis of the search space and the speed with which the GA finds a solution. The range of document types for which this method produces attractive layouts is considered, and finally suggestions are made for future work, which would make the system into a more complete layout generation tool. The key novel ideas in this thesis are summarised in a patent application entitled 'Page composition' submitted by Hewlett- Packard to the UK Patent Office on Friday 30th August 2002.
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