基于自适应遗传算法的矩形排样方法研究

Research on Rectangle Nesting Method Based on Adaptive Genetic Algorithm

将自适应遗传算法应用于矩形排样问题,求解最优的排样方案。首先建立矩形排样问题的模型,使用最低水平线算法将问题变为求解矩形最优放置顺序的问题。应用遗传算法针对矩形排样问题进行求解。通过改进自适应策略改变交叉和变异概率使遗传算法的性能得到优化。最后在Matlab环境下进行编程和仿真。经过仿真验证可以求解出一种优秀的矩形排样方案,且自适应遗传算法的性能优于普通遗传算法。

Adaptive genetic algorithm is used to solve the rectangle nesting problem.First,the model of the rectangle nesting problem is built and the lowest horizontal line algorithm is used to transform the problem into a rectangular placement sequence problem.The genetic algorithm is applied to solve the rectangle nesting problem.The performance of the genetic algorithm is optimized by improved adaptively changing the crossover and mutation probabilities.Finally,programming and simulation are performed in the Matlab environment.Through simulation experiments,an excellent rectangle nesting project can be obtained and the performance of adaptive genetic algorithm can be verified to be better than ordinary genetic algorithm.