This paper proposes an iteratively doubling local search approach for the two-dimensional irregular bin packing problem (2DIRBPP) with limited rotations, whose objective is to pack a given set of irregular pieces into the minimum number of rectangular bins. The allowable angles of each piece are limited. To solve this problem, a waste least first decreasing strategy is introduced to assign the piece to the bins. A simple greedy local search approach by moving the pieces from one bin to another is utilized to improve the solution. We adapt an overlap minimization approach to solving the one bin placement problem. The classical bottom-left method is utilized to generate the initial position for each piece, and the random local search by exchanging the positions of two pieces is used to minimize the overlap. Moreover, a novel warm start and an iteratively doubling search strategy are proposed to speed up the search process. The standard benchmark results show that our approach improves the results for most of the instances in the literature.

本文针对旋转受限的二维不规则装箱问题 (2DIRBPP) 提出了一种迭代加倍局部搜索方法，其目标是将一组给定的不规则块装入最少数量的矩形箱中。每件允许的角度是有限的。为了解决这个问题，引入了一种浪费最少的减少策略来将碎片分配到垃圾箱。通过将碎片从一个 bin 移动到另一个 bin 的简单贪婪本地搜索方法用于改进解决方案。我们采用重叠最小化方法来解决单箱放置问题。经典的左下角方法用于生成每块的初始位置，并通过交换两块位置的随机局部搜索来最小化重叠。而且，提出了一种新颖的热启动和迭代加倍搜索策略来加快搜索过程。标准基准测试结果表明，我们的方法改善了文献中大多数实例的结果。