This article proposes a novel discrete grey wolf optimization for the packing problem, called the two-dimensional strip packing (2DSP) problem without guillotine constraint. The 2DSP involves cutting pieces from a stock sheet with the objective of minimizing waste. To solve the 2DSP problem by the discrete grey wolf algorithm, many strategies are originally proposed. The searching and attacking operators in the algorithm are redesigned to guarantee coding effectiveness. A novel approach to measure the distance between the wolves is presented. In addition, an improved best-fit strategy is developed to solve this packing problem. The best-fit strategy divides the situation into five cases based on the width and length of the rectangle. Computational results on widely used benchmark instances show that the novel discrete grey wolf algorithm can solve the 2DSP problem effectively, and surpasses most of the previously reported meta-heuristic algorithms.

中文翻译：

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一种求解装箱问题的有效离散灰狼优化算法

本文针对打包问题提出了一种新颖的离散灰狼优化，称为无断头台约束的二维条带打包 (2DSP) 问题。2DSP 涉及从库存片材切割件，目的是最大限度地减少浪费。为了通过离散灰狼算法解决2DSP问题，最初提出了很多策略。重新设计了算法中的搜索和攻击算子，以保证编码的有效性。提出了一种测量狼之间距离的新方法。此外，还开发了一种改进的最佳拟合策略来解决此包装问题。最佳拟合策略根据矩形的宽度和长度将情况分为五种情况。