A Knowledge Based System for Minimum Rectangle Nesting
Nesting algorithms deal with the optimal placement of shapes in specified regions subject to specified constraints. In this paper, a complex algorithm for solving two-dimensional nesting problem is proposed. Arbitrary geometric shapes are first quantized into a binary form. These binary representations are subsequently processed by operators which nest the shapes in a rectangle of minimum area. After nesting is completed, the binary representations are converted back to the original geometric form. Investigations have shown that the nesting effect is driven by quantization accuracy. Therefore, better accuracy is possible given more computing time. However, the proposed knowledge based system can significantly reduce the time of nesting, by intelligently pairing shapes, based on prior knowledge of their form.
Algorithms; Binary quantization; Computer algorithms; Expert systems (Computer science); Forms; Binary; Geometric quantization; Knowledge based system; Nesting
Computer and Systems Architecture | Computer Engineering | Electrical and Computer Engineering | Engineering
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A Knowledge Based System for Minimum Rectangle Nesting. In Juan D. Velásquez; Sebastián A. Ríos; Robert J. Howlett; Lakhmi C. Jain,
Knowledge-Based and Intelligent Information and Engineering Systems
Springer Berlin Heidelberg.