Abstract: Order picking is the most time-consuming job in the distribution center.The distribution speed is not only the core competitiveness of the new e-commerce but also the KPI of material distribution of large-scale manufacturing enterprises.The mixed picking strategy has become an important way to improve the distribution speed.The goods were classified according to the degree of urgency of shipment,and a multi-objective optimization model of stacker picking sequence was established with the minimum objective function of energy cost,operation time and shipment penalty.An fast elitist Non-dominant Sorting Genetic Algorithm (NSGA-Ⅱ) was presented.The experiments showed that most the orders could been completed ahead under the mixed picking strategy.The improved optimization algorithm could provide decision makers with scientific decision-making basis in the three dimensions of cost,efficiency and service quality.

Key words: mixed picking strategy, multi-objective optimization, picking sequence optimization, fast elitist non-dominant sorting genetic algorithm, Pareto solution set, autormatic stacker

摘要： 订单拣选是配送中心最费时费力的环节,配送速度不仅是新型电商的核心竞争力也是大型制造企业物料配送的核心指标,复合式拣选策略成为提高配送速度的重要方式。结合复合式拣选方式中货物之间不同的出货要求,将货物按照出货的紧急程度进行分类,建立了以能耗成本、作业时间以及出货惩罚值最小化为目标的堆垛机拣选作业序列多目标优化模型。通过改进带精英策略的非支配排序遗传算法(NSGA-Ⅱ)实现该问题的高效求解。算例分析表明,复合式拣选策略下可实现大多数订单的提前拣选,改进优化算法可为决策者在成本、效率和服务质量3个维度提供科学决策依据。

关键词: 复合拣选策略, 多目标优化, 拣选序列优化, 带精英策略的非支配排序遗传算法, Pareto解集, 堆垛机