Recently, market has witnessed a tremendous growth in E-commerce sales, which bring tons of opportunities as well as challenges. Warehouses have to handle unique characteristics of customer orders in the era of E-commerce which consists of small order scales, large items count, unexpected irregular order arrival patterns, seasonality demand peeks, and high service level expectations. Warehouses are adopting wave-picking as an effective policy composed of item-batching, load-assignment and picker-routing problems. In this research, principle combination of load-assignment and picker-routing problems is studied. A mixed integer mathematical model is established based on features of a wave-picking warehouse. In order to conquer the complexity caused by routing decision of the proposed problem, a set of effective modified Estimation Distribution Algorithms is developed. The set of proposed algorithms is proved to have stable gaps (1% on average and maximum less than 2%) compared with Cplex 12.8, while can be solved in much larger scale within quite short time (100 pickers and 350 items in each wave within less than 2 min).

最近，市场见证了电子商务销售的巨大增长，带来了无数的机遇和挑战。在电子商务时代，仓库必须处理客户订单的独特特征，其中包括小订单规模，大物品数量，意料之外的不规则订单到达模式，季节性需求透视和高服务水平期望。仓库采用拣货作为一项有效的政策，包括分批处理，分配货物和拣选路线。在这项研究中，研究了负荷分配和拣选路线问题的原理组合。基于选波仓库的特点，建立了混合整数数学模型。为了克服所提出问题的路由决策而导致的复杂性，开发了一套有效的改进的估计分布算法。与Cplex 12.8相比，该套算法被证明具有稳定的差距（平均1％，最大小于2％），并且可以在相当短的时间内以更大的规模解决（每波内100个选择器和350个项目）少于2分钟）。