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Approximate and exact algorithms for the double-constrained two-dimensional guillotine cutting stock problem

机译:双约束二维断头台切料问题的近似和精确算法

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In this paper, we propose approximate and exact algorithms for the double constrained two-dimensional guillotine cutting stock problem (DCTDC). The approximate algorithm is a two-stage procedure. The first stage attempts to produce a starting feasible solution to DCTDC by solving a single constrained two dimensional cutting problem, CDTC. If the solution to CTDC is not feasible to DCTDC, the second stage is used to eliminate non-feasibility. The exact algorithm is a branch-and-bound that uses efficient lower and upper bounding schemes. It starts with a lower bound reached by the approximate two-stage algorithm. At each internal node of the branching tree, a tailored upper bound is obtained by solving (relaxed) knapsack problems. To speed up the branch and bound, we implement, in addition to ordered data structures of lists, symmetry, duplicate, and non-feasibility detection strategies which fathom some unnecessary branches. We evaluate the performance of the algorithm on different problem instances which can become benchmark problems for the cutting and packing literature.
机译:在本文中,我们为双约束二维断头台切削料问题(DCTDC)提出了近似和精确的算法。近似算法是一个两阶段过程。第一阶段试图通过解决一个约束二维切割问题CDTC来为DCTDC提出一个可行的解决方案。如果CTDC的解决方案对于DCTDC不可行,则使用第二阶段来消除不可行性。确切的算法是使用有效的上下限方案的分支定界法。它以近似两阶段算法达到的下限开始。在分支树的每个内部节点处,通过解决(松弛)背包问题来获得定制的上限。为了加速分支和边界,除了实现列表的有序数据结构之外,我们还实现了对称,重复和非可行性检测策略,这些策略使一些不必要的分支难以理解。我们评估算法在不同问题实例上的性能,这些实例可能成为切割和包装文献的基准问题。

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