Study on Cutting Stock Optimization for Decayed Wood Board Based on Genetic Algorithm

Abstract

When making wood boards, the defects on the boards can reduce the strength of timber, and influence the ma- chining process automation degree as well as the decoration quality or appearance after processing. Therefore, how to re- move 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 combina- tion 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 utiliza- tion rate reached 95.9%, which greatly improved the utilization rate of wood.