解家纺企业生产计划问题的并行混合遗传算法

为解决家纺企业的实际车间批量生产计划问题，提出了一个基于自然编码的混合遗传算法。此算法具有如下特点：一方面编码方式能有效地反映调度方案；另一方面对每子代得到的调度方案利用爬山算法对其进行了局部调整，大大加快了收敛速度。同时为了更好地适应调度实时性和解大型企业此类问题的需要，基于遗传算法自然并行性特点的基础上，实现了主从式控制网络模式下并行混合遗传算法。计算结果表明，此算法是有效的，有着较高的并行性，并能适用于解大型此类企业车间批量生产计划问题，在实际应用中有着较广阔地应用前景。

Parallel Hybrid Genetic Algorithm for Solving Production Planning Problems in Textile Enterprises

In order to solve workshop mass production planning problem in a kind of textile enterprises, a hybrid genetic algorithm based on natural coding method was suggested. The algorithm has the following characteristics: on one hand, its coding method can effectively reflect the virtual scheduling policy; on the other hand, a climbing method is adopted to adjust its local solutions to speed its convergence. Meanwhile, under the mode of master-slave control networks, a parallel hybrid genetic algorithm is applied in order to adapt to lager scale and real-time scheduling problems of these enterprises. The computational results show that it is effective, and has much better parallel characteristics. In a word, the method can be applied to solve larger scale workshop mass production planning problems of this kind of textile enterprises and a much better prospect of application can be optimistically expected.