基于改进遗传算法的自动拣选系统 拣选位分配建模与优化

针对某自动拣选系统建立了拣选位分配优化模型，以拣选时间模型作为适应度函数，并通过判断海明距离添加一个惩罚函数对遗传算法进行了改进，对算例进行仿真实验，可以得到货位排序优化后，总拣选时间明显降低了27.85%。结果表明，货物拣选位的分配对自动拣选系统的拣选效率有很大的影响。要想降低总拣选时间，提高自动拣选系统的拣选效率，不能只考虑个别种类货物的位置分配，要从全局的方向去考虑。该研究对配送中心如何提高自动拣选系统的效率提供了理论支持。

Modeling and Optimization of Picking Location Allocation in Automatic Picking System Based on Improved Genetic Algorithm

An optimization model of picking location allocation is established for an automatic picking system. The picking time model is used as the fitness function, and the genetic algorithm is improved by adding a penalty function to judge the Heming distance. The simulation results show that the total picking time is obviously reduced by 26.25% after the optimization of the picking location. The results show that the distribution of goods picking position has a great influence on the efficiency of automatic picking system. In order to reduce the total picking time and improve the efficiency of automatic picking system, not only the location distribution of individual goods, but also the overall direction should be considered. This research has strong practical significance and provides theoretical support for improving the efficiency of the automatic picking system in distribution centers.