基于双种群遗传算法的智能排样系统

Intelligent nesting system with dual-population genetic algorithm

研究并改进了基于双种群遗传算法的矩形优化排样问题的求解方法。使用不同方式产生初始种群,对不同个体使用不同的具有自适应能力的交叉算子和变异算子,使算法的全局优化能力得到提高。以该算法为基础开发了一个应用于实际生产的智能排样系统,对比文献中的数据进行验证,结果表明在原材料利用率方面本方法高于其他类似的正交排样算法。

The dual population genetic algorithm for rectangular packing problems was studied and improved.Two initial populations were generated in different ways in this algorithm.Each population was given to a different adaptive crossover operator and mutation operator which made the algorithm＇s ability of global optimization got a great improvement.An intelligent nesting system used in actual production was developed based on the improved dual-population genetic algorithm.In order to verify the performance of the algorithm,some datas were taken from the literature and tested.The examples show that the algorithm performs better than other similar algorithms to solve the problems of rectangular orthogonal layout in the utilization of raw materials.