The rectangular cutting problem is a branch of the two-dimensional cutting problems.
矩形件排样问题，是二维下料问题的一个分支。
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。
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。
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。
In this thesis, genetic algorithms are studied from coding. On the basis of the study genetic algorithms are applied to solving one-dimensional cutting stock problems.
本篇论文在对遗传算法进行分析和研究的基础上，把遗传算法用于一维下料问题的求解。
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。
The two-dimensional cutting problems of rectangular and irregular blanks have been studied intensively, but the cutting problems of circular blanks have drawn little attention.
本文研究的是圆形件排样问题，是二维下料问题的一个分支。
As for the one-dimensional cutting problem, the paper comes up with a model of mutual deadline, in allusion to which, a new algorithm is put forward, that is, DP greedy algorithm.
对于一维下料问题，本文得到一个有各自交货时间的模型。针对该模型提出一种新的算法：DP贪婪算法。
As for the one-dimensional cutting problem, the paper comes up with a model of mutual deadline, in allusion to which, a new algorithm is put forward, that is, DP greedy algorithm.
对于一维下料问题，本文得到一个有各自交货时间的模型。针对该模型提出一种新的算法：DP贪婪算法。
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