Extended local search algorithm based on nonlinear programming for two-dimensional irregular strip packing problem

This paper presents an extended local search algorithm (ELS) for the irregular strip packing problem. It adopts two neighborhoods, swapping two given polygons in a placement and placing one polygon into a new position. The local search algorithm is used to minimize the overlap on the basis of the neighborhoods mentioned above and the unconstrained nonlinear programming model is adopted to further minimize the overlap during the search process. Moreover, the tabu search algorithm is used to avoid local minima, and a compact algorithm is presented to improve the result. The results of standard test instances indicate that when compared with other existing algorithms, the presented algorithm does not only show some signs of competitive power but also updates several best known results.     

正三角形容器内等圆Packing问题的启发式算法

等圆Packing问题研究如何将n个单位半径的圆形物体互不嵌入地置入一个边长尽量小的正三角形容器内,作为一类经典的NP难度问题,其有着重要的理论价值和广泛的应用背景.模拟退火算法是一种随机的全局寻优算法,通过将启发式格局更新策略与基于梯度法的局部搜索策略融入模拟退火算法,并与二分搜索相结合,提出一种求解正三角形容器内等圆Packing问题的启发式算法.该算法将启发式格局更新策略用来产生新格局和跳坑,用梯度法搜索新产生格局附近能量更低的格局,并用二分搜索得到正三角形容器的最小边长.对41个算例进行测试的实验结果表明,文中算法改进了其中38个实例的目前最优结果,是求解正三角形容器内等圆Packing问题的一种有效算法.     

Scandinavian Thins on Top of Cake: New and Improved Algorithms for Stacking and Packing

We show how to compute the smallest rectangle that can enclose any polygon, from a given set of polygons, in nearly linear time; we also present a PTAS for the problem, as well as a linear-time algorithm for the case when the polygons are rectangles themselves. We prove that finding a smallest convex polygon that encloses any of the given polygons is NP-hard, and give a PTAS for minimizing the perimeter of the convex enclosure. We also give efficient algorithms to find the smallest rectangle simultaneously enclosing a given pair of convex polygons.     

Multiple Translational Containment Part I: An Approximate Algorithm

We present an algorithm for finding a solution to the two-dimensional translational approximate multiple containment problem: find translations for k polygons which place them inside a polygonal container so that no point of any polygon is more than 2ε inside of the boundary of any other polygon. The polygons and container may be nonconvex. The value of ε is an input to the algorithm. In industrial applications the containment solution acts as a guide to a machine cutting out polygonal shapes from a sheet of material. If ε is chosen to be a fraction of the cutter's accuracy, then the solution to the approximate containment problem is sufficient for industrial purposes. Given a containment problem, we characterize its solution and create a collection of containment subproblems from this characterization. We solve each subproblem by first restricting certain two-dimensional configuration spaces until a steady state is reached, and then testing for a solution inside the configuration spaces. If necessary, we subdivide the configuration spaces to generate new subproblems. The running time of our algorithm is , where s is the largest number of vertices of any polygon generated by a restriction operation. In the worst case s can be exponential in the size of the input, but, in practice, it is usually not more than quadratic. Received June 24, 1994; revised August 22, 1995.     

允许自由旋转的2个简单多边形匹配算法

为了解决二维不规则排料问题中的匹配问题,提出了一种允许自由旋转条件下,2个无孔洞的简单多边形之间的匹配算法.该算法基于2个多边形可以自由旋转的假设,对它们之间NFP为凹或凸的情况,选择适当的匹配方法,找出一种使得其匹配后空隙尽可能小,同时保证其整体的矩形的规整度也较高的匹配方案;并用匹配空隙的利用率、匹配后整体面积的利用率,以及匹配后整体的矩形规整度等多个指标来衡量匹配的效果.实验选择于ESICUP中的部分代表性的多边形样例与多个算法进行对比实验,结果表明,该算法在任意旋转精度的要求下,均具有运行速度快的特点,可以很好地应用于服装排料等实际问题.     

Using extended feature objects for partial similarity retrieval

In this paper, we introduce the concept of extended feature objects for similarity retrieval. Conventional approaches for similarity search in databases map each object in the database to a point in some high-dimensional feature space and define similarity as some distance measure in this space. For many similarity search problems, this feature-based approach is not sufficient. When retrieving partially similar polygons, for example, the search cannot be restricted to edge sequences, since similar polygon sections may start and end anywhere on the edges of the polygons. In general, inherently continuous problems such as the partial similarity search cannot be solved by using point objects in feature space. In our solution, we therefore introduce extended feature objects consisting of an infinite set of feature points. For an efficient storage and retrieval of the extended feature objects, we determine the minimal bounding boxes of the feature objects in multidimensional space and store these boxes using a spatial access structure. In our concrete polygon problem, sets of polygon sections are mapped to 2D feature objects in high-dimensional space which are then approximated by minimal bounding boxes and stored in an R-tree. The selectivity of the index is improved by using an adaptive decomposition of very large feature objects and a dynamic joining of small feature objects. For the polygon problem, translation, rotation, and scaling invariance is achieved by using the Fourier-transformed curvature of the normalized polygon sections. In contrast to vertex-based algorithms, our algorithm guarantees that no false dismissals may occur and additionally provides fast search times for realistic database sizes. We evaluate our method using real polygon data of a supplier for the car manufacturing industry. Edited by R. Güting. Received October 7, 1996 / Accepted March 28, 1997     

An improved method for calculating the no-fit polygon

The no-fit polygon (NFP) is the set of feasible locations that one polygon may take with respect to another polygon, such that the polygons do not overlap. Feasible locations are required for most of the solutions to two-dimensional packing problems, and also for other problems such as robot motion planning.     

计算多边形交集、并集面积的算法

平面多边形交集与并集面积的计算机算法可以利用多边形裁剪算法来实现。本文提出的算法思想是利用Weiler-Atherton多边形裁剪算法中的多边形链表,在遍历链表时遇到交点就改变跟踪方向,这样可以求出并集顶点表,求交集时只要从入点开始跟踪遇到交点再改变跟踪方向;最后,通过交集和并集表求出它们的面积。多边形可以是凸的或凹的、甚至是带孔的。     

基于夹边边对的凸多边形间快速相交检测算法

本文在对现有的相交检测算法进行研究的基础上,提出了基于夹边边对的空间平面凸多边形快速相交检测算法,为平面凸多边形间判交问题提供了一致的计算方法,并将算法的应用对象扩展到任意空间平面凸多边形。该算法分为两步：第一步,确定所要检测的两个凸多边形是否都存在相对于另一凸多边形所在平面的夹边边对,如果至少一个凸多多边形中不存在相对于另一凸多边形所在平面的夹边边对,那么立即返回两个多边形不相交;第二步,根据前面计算得到的两个凸多边形中的夹边边对,计算两组边对间对应夹边的符号距离判断两个多边形是否相交     

Translational polygon containment and minimal enclosure using mathematical programming

A new algorithm is given for the two-dimensional translational containment problem: find translations for k polygons which place them inside a polygonal container without overlapping. Both the polygons and the container can be non-convex. The algorithm is based on mathematical programming principles. The containment algorithm is generalized to solve minimal enclosure problems: find the minimal area enclosing square or minimal area enclosing rectangle for k translating polygons. The containment algorithm consists of new algorithms for restriction , evaluation , and subdivision of two-dimensional configuration spaces. Restriction establishes lower bounds through relaxation and the solution of linear programs. Evaluation establishes upper bounds by finding potential solutions. Subdivision branches, when necessary, by introducing a cutting plane. The algorithm shows that either the upper bound of the objective (overlap) is exactly zero or the lower bound is greater than zero. Hence, it gives an exact solution to the containment problem. Experiments show that new containment algorithm clearly outperforms purely geometric containment algorithms. For data sets from the apparel industry, it can solve containment for up to ten non-convex polygons in practice. An implementation of the algorithm given in this paper has been licensed by Gerber Garment Technologies, the largest provider of textile CAD/CAM software in the US, and they are incorporating it into an existing CAD/CAM software product.     

基于夹角变化趋势的多边形自动搜索和生成算法

利用左转算法生成多边形是GIS中面域组织和拓扑关系建立的常用算法。根据算法规则,对于由顺时针方向和逆时针方向建立的多边形都可以生成多边形文件,这就会产生一些重复多边形和无效的多边形。为此,提出了基于夹角变化趋势判断多边形搜索方向的算法,根据左转或右转算法得到的点组顺序,分别计算由起始点出发的弧段的方位角,根据相邻弧段夹角的和来判断多边形的搜索方向,实现了每一多边形都是由左转算法生成,完成了多边形的自动建立。该算法有效地判断了多边形的搜索方向,避免了无效多边形的生成。     

An exact algorithm for minimizing vertex guards on art galleries

We consider the problem [art gallery problem (AGP)] of minimizing the number of vertex guards required to monitor an art gallery whose boundary is an n‐vertex simple polygon. In this paper, we compile and extend our research on exact approaches for solving the AGP. In prior works, we proposed and tested an exact algorithm for the case of orthogonal polygons. In that algorithm, a discretization that approximates the polygon is used to formulate an instance of the set cover problem, which is subsequently solved to optimality. Either the set of guards that characterizes this solution solves the original instance of the AGP, and the algorithm halts, or the discretization is refined and a new iteration begins. This procedure always converges to an optimal solution of the AGP and, moreover, the number of iterations executed highly depends on the way we discretize the polygon. Notwithstanding that the best known theoretical bound for convergence is Θ(n³) iterations, our experiments show that an optimal solution is always found within a small number of them, even for random polygons of many hundreds of vertices. Herein, we broaden the family of polygon classes to which the algorithm is applied by including non‐orthogonal polygons. Furthermore, we propose new discretization strategies leading to additional trade‐off analysis of preprocessing vs. processing times and achieving, in the case of the novel Convex Vertices strategy, the most efficient overall performance so far. We report on experiments with both simple and orthogonal polygons of up to 2500 vertices showing that, in all cases, no more than 15 minutes are needed to reach an exact solution, on a standard desktop computer. Ultimately, we more than doubled the size of the largest instances solved to optimality compared with our previous experiments, which were already five times larger than those previously reported in the literature.     

An exact strip packing algorithm based on canonical forms

Given a set of rectangles and a rectangular container with a fixed width, called a strip, the two-dimensional strip packing problem (2SP) requires all the given rectangles to be placed orthogonally without overlap within the strip so as to minimize the height of the strip. 2SP and its variants have many applications in steel and textile industries, including an indirect application in scheduling problems. However, 2SP is known to be NP-hard.     

基于凸剖分的多边形窗口线裁剪算法

以不增加新点的方式将多边形剖分为一些凸多边形,并基于这些多边形的边建立二叉树进行管理.裁剪计算时,根据二叉树快速地找到与被裁剪线有相交的凸多边形,然后运用高效的凸多边形裁剪算法进行线裁剪.该方法能自适应地降低裁剪计算的复杂度,使其在O(logn)和O(n)之间变化,并在大多数情况下小于O(n),其中n是多边形边数.虽然该方法需要进行预处理,但在许多应用(如多边形窗口对多边形的裁剪)中,其总执行时间(包括预处理时间和裁剪时间)比已有的不需要预处理的裁剪算法少很多.     

缺陷板材非规则件优化排样

针对理论上属于NPC 问题的非规则件优化排样问题,论文提出一种基于 小生境技术的自适应遗传模拟退火算法与基于内靠接临界多边形最低点的启发式布局算法 相结合的方法。考虑到算法中交叉概率和变异概率的选择影响到算法收敛性,提出了自适应 的交叉概率和变异概率,通过基于小生境技术的遗传模拟退火算法对非规则件排样的最优顺 序和各自的旋转角度进行优化搜索。将非规则件定位在有缺陷原材料和非规则件多边形的内 靠接临界多边形最低点以实现个体的解码,同时避开了原材料表面缺陷。排样实例表明,该 优化排样算法行之有效,具有广泛的适应性。     

Optimality and competitiveness of exploring polygons by mobile robots

A mobile robot, represented by a point moving along a polygonal line in the plane, has to explore an unknown polygon and return to the starting point. The robot has a sensing area which can be a circle or a square centered at the robot. This area shifts while the robot moves inside the polygon, and at each point of its trajectory the robot “sees” (explores) all points for which the segment between the robot and the point is contained in the polygon and in the sensing area. We focus on two tasks: exploring the entire polygon and exploring only its boundary. We consider several scenarios: both shapes of the sensing area and the Manhattan and the Euclidean metrics.We focus on two quality benchmarks for exploration performance: optimality (the length of the trajectory of the robot is equal to that of the optimal robot knowing the polygon) and competitiveness (the length of the trajectory of the robot is at most a constant multiple of that of the optimal robot knowing the polygon). Most of our results concern rectilinear polygons. We show that optimal exploration is possible in only one scenario, that of exploring the boundary by a robot with square sensing area, starting at the boundary and using the Manhattan metric. For this case we give an optimal exploration algorithm, and in all other scenarios we prove impossibility of optimal exploration. For competitiveness the situation is more optimistic: we show a competitive exploration algorithm for rectilinear polygons whenever the sensing area is a square, for both tasks, regardless of the metric and of the starting point. Finally, we show a competitive exploration algorithm for arbitrary convex polygons, for both shapes of the sensing area, regardless of the metric and of the starting point.     

Waste minimization in irregular stock cutting

This paper addresses a category of two dimensional NP-hard knapsack problem in which a given convex/non-convex planner items (polygons) have to be cut out of a single convex/non-convex master surface (stock). This cutting process is found in many industrial applications such as sheet metal processes, home-textile, garment, wood, leather and paper industries. An approach is proposed to solve this problem, which depends on the concept of the difference between the area of a collection of polygons and the area of their convex hull. The polygon assignment inside the stock is subjected to feasibility tests to avoid overlapping, namely, angle test, bound test, point inclusion and polygon intersection test. An iterative scheme is used to generate different polygon placements while optimizing the objective function. Computer software is developed to solve and optimize the problem under consideration. Few examples are conducted for different combinations of convex, non-convex items and stocks. Well-known benchmark problems from the literature are tested and compared with our approach. The results of our algorithm have an interesting computational time and can compete with the results of previous work in some particular problems. The computational performance of the developed software indicates the efficiency of the algorithm for solving 2-D irregular cutting of non-convex polygons out of non-convex stock.     

求解简单多边形间最小距离的一个线性时间算法

计算简单多边形间的最小距离,在所有与几何图形计算有关的领域中,一直以来都是一个基本问题。为了更快地求解简单多边形的最小距离,提出了一个基于关联多边形三角化分割的简单多边形间最小距离的求解算法。该算法的主要思想是:首先构造一个关联多边形把两个多边形联系起来,其目的是把最小距离限制在这个关联多边形内;然后根据两个多边形的最小边界矩形包围框间的不同位置关系,详细阐述了关联多边形的构造过程,同时论述了关联多边形是一个简单多边形。为了计算最小距离,首先要对关联多边形进行三角化分割,并使最小距离位于三角化分割结果中某一个三角形区域内,或者至多位于两个相邻三角形区域内;之后通过对所有三角形进行遍历来找出最小距离及其所在的位置。该算法的时间复杂度是线性的。     

Approximate Guarding of Monotone and Rectilinear Polygons

We show that vertex guarding a monotone polygon is NP-hard and construct a constant factor approximation algorithm for interior guarding monotone polygons. Using this algorithm we obtain an approximation algorithm for interior guarding rectilinear polygons that has an approximation factor independent of the number of vertices of the polygon. If the size of the smallest interior guard cover is OPT for a rectilinear polygon, our algorithm produces a guard set of size O(OPT ²).     

The crossing function and its application to zig-zag tool paths

In zig-zag paths, which are used to sweep planar areas in applications such as machining and surveillance, the number of switch-backs in the path is a major contributor to cutting time. We develop algorithms to pick the direction in which a zig-zag path on a polygon will have the minimum number of switch-backs. We introduce the concept of a crossing function of a two-dimensional contour, which is a measure of how many times a finely pitched set of parallel raster-lines at some angle intersects with the contour. We show that minimizing the crossing-function minimizes the number of switch-backs. We then show that for polygons, the crossing-function is minimized at a finite set of orientations parallel to the edges of the polygon. We show that the problem of minimizing the crossing function can be reduced to minimizing the width of an equivalent convex polygon, and develop an algorithm that takes n log(n) time for an n-sided polygon. Finally, we discuss how these algorithms are useful in machining.