The digital networked world is enabling and requiring a new emphasis on personalized document creation. The new, more dynamic digital environment demands tools that can reproduce both the contents and the layout automatically, tailored to personal needs and transformed for the presentation device, and can enable novices to easily create such documents. In order to achieve such automated document assembly and transformation, we have formalized custom document creation as a multiobjective optimization problem, and use a genetic algorithm to assemble and transform compound personalized documents. While we have found that such an automated process for document creation opens new possibilities and new workflows, we have also found several areas where further research would enable the approach to be more broadly and practically applied. This paper reviews the current system and outlines several areas where future research will broaden its current capabilities.

In our previous paper, we have shown that case-based reasoning (CBR) techniques can be used as a viable formulation for solving assembly sequence generation problems. The issues covered in that paper were case base organization, case selection and matching, and case indexing. The part on case adaptation was not addressed in a formal way to allow satisfactory generalization of the method to a large class of assembly planning problems. We present in this paper a methodology which formalizes the adaptation process of CBR using constraint satisfaction techniques. Combining CBR with constraint satisfaction provides a generalized formalism for assembly planning problem solving.