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Solving two-dimensional cutting stock problem via a DNA computing algorithm

机译:通过DNA计算算法解决二维切割股票问题

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Two-dimensional cutting stock problem (TDCSP) is a well-known combinatorial optimization problem in which a given set of two-dimensional small pieces with different shapes should be cut from a given main board so that the demand of each small piece is satisfied and the total waste is minimized. Since TDCSP is an NP-complete problem, it is unsolvable in polynomial time on electronic computers. However, using the structure of DNA molecules, DNA computing algorithms are capable to solve NP-complete problems in polynomial time. In this paper, a DNA computing algorithm based on the sticker model is presented to find the optimal solution to TDCSP. It is proved that the time complexity of this algorithm on DNA computers is polynomial considering the number of small pieces and the length and width of the main board.
机译:二维切割股票问题(TDCSP)是一种众所周知的组合优化问题,其中应从给定的主板切割具有不同形状的给定的二维小块组,使得满足每个小件的需求和总废物最小化。由于TDCSP是一个NP完全的问题,因此在电子计算机上的多项式时间内无法解决。然而,使用DNA分子的结构,DNA计算算法能够解决多项式时间中的NP完全问题。本文提出了一种基于贴纸模型的DNA计算算法,以找到TDCSP的最佳解决方案。事实证明,考虑到主板的小块数量和长度和宽度,该算法对DNA计算机上该算法的时间复杂性是多项式。

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