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林业科学 ›› 2014, Vol. 50 ›› Issue (6): 181-186.doi: 10.11707/j.1001-7488.20140624

• 研究简报 • 上一篇    下一篇

基于分组降维规则和遗传算法的人造板材矩形件优化下料方法

张国梁1,2,3, 侯晓鹏1,3, 苗虎1,3, 安源1,3, 周玉成1,3, 姚永和4   

  1. 1. 中国林业科学研究院林业新技术研究所 北京 100091;
    2. 河北农业大学林学院 保定 071000;
    3. 中国林业科学研究院木材工业研究所 北京 100091;
    4. 上海跃通木工机械设备有限公司 上海 201505
  • 收稿日期:2013-12-13 修回日期:2014-02-12 出版日期:2014-06-25 发布日期:2014-07-07
  • 基金资助:

    中国林业科学研究院林业新技术所基本科研业务费专项(CAFINT2012K01)。

Layout Method of Rectangular Wood Based Panel Parts Based on Grouping and Dimension Reducing Heuristic Rule and Genetic Algorithm

Zhang Guoliang1,2,3, Hou Xiaopeng1,3, Miao Hu1,3, An Yuan1,3, Zhou Yucheng1,3, Yao Yonghe4   

  1. 1. Research Institute of Forestry New Technology, CAF Beijing 100091;
    2. College of Forestry, Agricultural University of Hebei Baoding 071000;
    3. Research Institute o f Wood Industry, CAF Beijing 100091;
    4. Shanghai Yuetong Woodworking Machine Equipment Co., Ltd., Shanghai 201505
  • Received:2013-12-13 Revised:2014-02-12 Online:2014-06-25 Published:2014-07-07
  • Contact: 侯晓鹏

关键词: 优化下料, 分组降维, 混合惩罚函数, 遗传算法

Abstract:

Algorithms which were available in most literatures for whole layout of large scale rectangular parts gave solutions that resulted in frequent change of saw line and therefore dropped sawing velocity down. To solve this problem, a grouping and dimension-reducing heuristic rule which took areas of rectangular parts as priority was put forward in this paper. According to this rule, no more than three kinds of rectangular parts were considered in each layout calculation. Corresponding mathematical model was set up. Hybrid punishment function that was the combination of interior point method and exterior point one was applied to deal with constrains. Genetic algorithm (GA) was adopted to search global optimal solution for layout. It was proved by example that the algorithm used in this paper could provide layout solution which exactly fulfilled guillotine cutting requirement and had saw line in order and therefore was useful to increase of sawing efficiency.

Key words: optimization layout, grouping and dimension-reducing, hybrid punishment function, genetic algorithm (GA)

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