因此，开展对二维矩形件优化排样问题的研究具有重要的理论意义和工程应用价值。
Therefore, research on the problem of two-dimensional optimal layout for rectangular parts is very important in theory and applications.
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。
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.
本算法适合应用于大批量、多种类的矩形零件在定宽无限长板材上的优化排样，获得了较好的优化排样方案；
This algorithm is suitable for optimized layout of rectangle parts with large amounts and many kinds and better optimized layout is got.
在研究矩形件优化排样数学模型的基础上，根据不同的下料的工艺要求，构造出与之相适应的四种不同的近似优化算法。
Based on researching mathematical model for optimal layout of rectangular piece, the paper constructs four optimal layout algorithms according to different processing technology conditions.
提出了一种基于离散粒子群优化算法求解矩形件排样问题的方法。
A discrete particle swarm algorithm for the rectangular strip packing problem is presented.
企业应用实例表明该方法是求解分段单一矩形优化排样问题的一个较为有效的方法。
Enterprise applications show that this method is an effective solution to the problem of single size rectangles packing.
对“一刀切”矩形件排样问题，提出一种将启发式递归与免疫克隆算法相结合的混合优化方法。
An optimal task scheduling model and an algorithm were brought forward, which combined the advantages of immune clonal algorithm and simulated annealing.
对“一刀切”矩形件排样问题，提出一种将启发式递归与免疫克隆算法相结合的混合优化方法。
An optimal task scheduling model and an algorithm were brought forward, which combined the advantages of immune clonal algorithm and simulated annealing.
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