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  2. Cricut - Wikipedia

    en.wikipedia.org/wiki/Cricut

    The original Cricut machine has cutting mats of 150 mm × 300 mm (6 in × 12 in), the larger Cricut Explore allows mats of 300 mm × 300 mm, and 300 mm × 610 mm (12 in × 12 in, and 12 in × 24 in). The largest machine will produce letters from a 13 to 597 mm (0.5 to 23.5 in) high.

  3. Mathematics of paper folding - Wikipedia

    en.wikipedia.org/wiki/Mathematics_of_paper_folding

    The fold-and-cut problem asks what shapes can be obtained by folding a piece of paper flat, and making a single straight complete cut. The solution, known as the fold-and-cut theorem, states that any shape with straight sides can be obtained. A practical problem is how to fold a map so that it may be manipulated with minimal effort or movements ...

  4. Cutting stock problem - Wikipedia

    en.wikipedia.org/wiki/Cutting_stock_problem

    This was an open problem until 2007, when an efficient algorithm based on dynamic programming was published. [14] The minimum number of knife changes problem (for the one-dimensional problem): this is concerned with sequencing and permuting the patterns so as to minimise the number of times the slitting knives have to be moved.

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  6. Fold-and-cut theorem - Wikipedia

    en.wikipedia.org/wiki/Fold-and-cut_theorem

    The corresponding problem that the theorem solves is known as the fold-and-cut problem, which asks what shapes can be obtained by the so-called fold-and-cut method. A particular instance of the problem, which asks how a particular shape can be obtained by the fold-and-cut method, is known as a fold-and-cut problem.

  7. Lazy caterer's sequence - Wikipedia

    en.wikipedia.org/wiki/Lazy_caterer's_sequence

    The maximum number of pieces from consecutive cuts are the numbers in the Lazy Caterer's Sequence. When a circle is cut n times to produce the maximum number of pieces, represented as p = f (n), the n th cut must be considered; the number of pieces before the last cut is f (n − 1), while the number of pieces added by the last cut is n.

  8. Maximum cut - Wikipedia

    en.wikipedia.org/wiki/Maximum_cut

    The canonical optimization variant of the above decision problem is usually known as the Maximum-Cut Problem or Max-Cut and is defined as: Given a graph G, find a maximum cut. The optimization variant is known to be NP-Hard. The opposite problem, that of finding a minimum cut is known to be efficiently solvable via the Ford–Fulkerson algorithm.

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