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。
One dimensional bin packing problem has many important applications such as multiprocessor scheduling, resource allocation, real world planning, and packing and scheduling optimization problems.
经典一维装箱问题在多处理器调度、资源分配和日常生活中的计划、包装、调度等优化问题中有着极为重要的应用。
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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