The relations among the board welding problem, knapsack problem and cutting stock problem are also discussed.
另外还讨论了拼板问题、背包问题和下料问题的关系。
The two-dimensional cutting stock problem is a problem about how to minimize the material input to pack all the blanks required.
求解二维下料问题即求解如何用最少的板材排入所需的全部毛坯的问题。
The cutting stock problem possesses important and widespread application in the engineering techniques and the industrial production.
“下料问题”在工程技术和工业生产中有着重要和广泛的应用。
With the rapid development of national economy in recent years, the one-dimensional cutting stock problem occurs in many industry areas.
近年来，随着国民经济的飞速发展，一维下料问题在建筑、电力、水利等领域获得了越来越广泛的应用。
This paper discusses the establishment and solution on the model of cutting stock problem and applies this model to production and practice.
论述了下料问题模型的建立及其求解，并把该模型应用于生产实践中。
Cutting stock problem has a wide spectrum of application. This paper gives a full description, classification and analyses the difficulty to solve the problem.
排样问题的应用范围非常广泛，本文从其应用领域、整体描述、名称、分类、求解难度等方面做了分析综述。
Cutting stock problem exits widely in production. Optimizing cutting stock is a method to improve the using rate of materials and to increase the benefit of industry.
下料问题在生产中普遍存在，优化下料可以提高原材料利用率，是企业增加经济效益的途径之一。
To resolve the rectangular cutting stock problem, this paper proposes a new greedy algorithm, based on analyzing the main disadvantage of the traditional approximate algorithm.
针对矩形件排样优化问题，分析了传统近似算法的主要缺陷，在此基础上，提出一种新的排样算法——贪婪算法。
Two-dimensional stock cutting problem can be settled by solving two one-dimensional knapsack problems, this paper presents a new algorithm based on the ant colony optimization idea.
基于一维问题的蚂蚁算法，本文将二维矩形件排样问题转化为一维背包问题，然后进行求解。
The paper based on the idea of K-OPT Algorithm for TSP, present a swap algorithm for the one-dimensional cutting-stock problem.
根据旅行商问题（TSP）的邻域搜索算法的思想，提出了型材下料问题的一种优化算法。
Rectangular stock cutting is the most applied problem in two-dimensional stock cutting problems which are widely existed in industrial application field.
在工业应用领域中存在大量的二维下料问题，其中应用最多的是矩形件下料问题。
One-dimensional cutting stock optimization and two-dimensional data sets optimal matching problem are mainly researched in this thesis.
本文主要研究了一维下料优化及二维数据集最佳匹配两大问题。
One-dimensional cutting stock optimization and two-dimensional data sets optimal matching problem are mainly researched in this thesis.
本文主要研究了一维下料优化及二维数据集最佳匹配两大问题。
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