Abstract

A hierarchical approach for nesting two-dimensional shapes based on genetic algorithms is described. For the higher-level search, a representation that facilitates genetic search based on recombination is developed. An alternatiye to overlap computation based on assembly of polygons is used at the lower level of search. Two implementations to find minimum-area enclosures for polygons, with and without a cohstraint on the width of stock, are discussed. Sample output illustrating the effectiveness of the approach is provided.

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