Slicing Trees

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# Slicing Trees

To store the actual pairs in every iteration step we use binary slicing trees. Every leaf of a tree represents a demand rectangle, an interior node of a tree represents a meta rectangle. Two nodes have the same father if the rectangles represented by these nodes are paired. In every node the shape function of the corresponding meta rectangle is stored.

A slicing tree is built bottom up. At the beginning of the algorithm all slicing trees consist of only one node (the root) representing the demand rectangles. In every iteration step, some of the trees are combined by a common father, which is the root of a new slicing tree representing the new meta rectangle. The iteration stops, if no more suitable pairs can be matched. A detailed description of this stop criteria is given in section six. Since all nodes contain a shape function and every shape function describes all possible layouts of a meta rectangle, the slicing trees contain an exponential number of possible layouts for the stock rectangles.

When the algorithm has ended, we can detect how the demand rectangles should be cut out of the stock rectangles. Therefore, a tree is traversed in top down order. Since every node stores a shape function we can detect how the first cut in the stock rectangle has to be made by considering the shape function in the root of a tree and searching for the first slicing instruction whose -value is smaller or equal to the width of the stock rectangle. Due to the property of the shape functions mentioned above, we automatically get the slicing instruction which describes the layout with the minimal length according to the made pairings. If the first cut has been carried out, the stock rectangle is split into two parts. The shape functions in the sons of the root describe how these two parts efficiently have to be split further. This proceeding is shown in Figure 5 by an example. By the traversal of all slicing trees (one slicing tree for every layout) the demand rectangles can be produced.

Figure 5:   Layout and corresponding slicing tree

Next: Maximum Weight Matching Up: Cutting Stock by Iterated Previous: Shape Functions

Andreas Fritsch
Mon Dec 19 14:08:31 MET 1994