Study on cutting stock optimization for decayed wood board based on genetic algorithm

被引：0
作者：
College of Engineering and Technology, Northeast Forestry University, Harbin [1 ]
Heilongjiang
150040, China
机构：
[1] College of Engineering and Technology, Northeast Forestry University, Harbin, 150040, Heilongjiang
来源：
Open Autom. Control Syst. J. | / 1卷 / 284-289期
关键词：
Cutting stock optimization; Defects; Genetic algorithm; Wood board;
D O I：
10.2174/1874444301507010284
中图分类号：
学科分类号：
摘要：
When making wood boards, the defects on the boards can reduce the strength of timber, and influence the machining process automation degree as well as the decoration quality or appearance after processing. Therefore, how to remove wood defects quickly and accurately and realize optimal cutting stock has always been a research hotspot in the field of wood processing. In this paper, based on the decayed wood board, the optimal scheme for cutting stock combination and mathematical model were designed, and the genetic algorithm that imitates the biology evolution was applied to code some optimization scheme initialized by chance. These schemes were improved by selection, crossover and mutation operation, and finally converged to the optimum. The results showed that genetic algorithm can achieve the cutting stock optimization for decayed wood boards. Through the realization of genetic algorithm in MATLAB, the wood board utilization rate reached 95.9%, which greatly improved the utilization rate of wood. © Wenshu et al.
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页码：284 / 289
页数：5
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