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。
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。
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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