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。
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。
应用推荐