摘要
现代自动分拣系统广泛采用先分区拣选后订单合流的分拣策略,其中存在着订单排序优化问题.对此,首先提出一种可压缩式订单合流方法,即提前各分区内订单货物的开始拣选时间,并在订单合流过程中将提前的拣选时间转化为对货物间距的压缩,从而既减少了订单总拣选时间,又避免了合单过程中货物的冲突.由于订单的拣选次序影响各订单的提前拣选时间,进而影响订单总拣选时间,故建立订单排序优化问题的数学模型并归结为旅行商问题(traveling salesman problem,TSP)问题,即各订单类似于待访问的城市,受订单排序影响的各订单拣选时间类似于各城市之间的距离,目标为求得合理的订单排序,从而使得总拣选时间最小.最后应用最大最小蚁群算法(max-minant system,MMAS)求解该模型.仿真结果显示,订单排序优化后自动分拣系统的拣选效率有了较大幅度的提高.
The modern automated sorting systems widely adopt the strategy of zone picking and order accumulation, where the order arrangement optimization problem exists. A reasonable order accumulation method was first presented to solve this problem, which can bring forward the start time of each order picking and transform it to the compression of goods during order accumulation. This method not only can reduce the total picking time of orders, but also can avoid the conflict of goods during order accumulation. As the sequence of order picking influences the start time of each order picking and the total picking time, a model was established for an order arrangement optimization problem, which can be referred to a traveling salesman problem （TSP）. These orders can be seen as the cities to travel in TSP, and each order＇ s picking time affected by order sequence can be seen as the distance between cities. The target is to find the least total picking time by means of optimizing the order sequence. A max-min ant system algorithm was utihzed to solve the model. The simulation result shows an obvious improvement of picking efficiency of the automated sorting system after order arrangement optimization.
出处
《山东大学学报（工学版）》
CAS
2008年第5期67-71,共5页
Journal of Shandong University（Engineering Science）
基金
国家自然科学基金资助项目(50175064)
关键词
自动分拣系统
订单合流
订单排序优化
最大最小蚁群算法
automated sorting system
order accumulation
order arrangement optimization
max-min ant system
