Study on One-Dimensional Wood Board Cutting Stock Problem Based on Adaptive Genetic Algorithm

When making wood board production, defects on board will influence the machining process automation degree. Therefore, how to fast, accurately remove of wood defects and realize optimal combination cutting stock problem has always been a research hotspot in the field of wood processing. According to the decayed wood board, the paper designed the one dimensional optimization cutting stock combined scheme and mathematical model, adopted the adaptive genetic algorithm imitating the biology evolution to code some optimization scheme initialized by chance, and improved these schemes by selection, crossover and mutation operation. At last these schemes converged to the optimum. The results showed that the adaptive genetic algorithm can achieve a good one dimensional wood board optimization cutting stock problem, through the realization of genetic algorithm in MATLAB, and makes the wood board utilization rate reached 98.9%.