Summary:With the booming development of e-commerce, order picking has become a key link to improve warehousing efficiency. Order picking includes two methods: order-by-order distribution and wave distribution. Order-by-order distribution is suitable for situations where the order quantity is small and the products are highly differentiated, while wave distribution improves efficiency by merging orders, and is especially suitable for situations where the order quantity is large and the products have high commonality. The order wave picking algorithm based on integer programming developed by Jiuzhang Intelligence aggregates orders based on SKU combinations and calculates the optimal order set under the specified number of goods. This algorithm aims to maximize the number of picking orders, while taking into account the range limitations of SKU combination and order quantity within the aggregation wave. For an order volume of approximately 122,000, it can aggregate approximately 95,500 orders within 20 seconds, covering 1,600 SKUs, providing an efficient solution for e-commerce warehousing operations.
1. What is order wave picking?
The rapid development of e-commerce has brought new challenges to the warehousing business. Order Picking is a key link, which refers to the process of selecting corresponding goods from the warehouse according to customer orders. This process is an important step to ensure that orders are processed and delivered to customers accurately, and directly affects the overall order fulfillment efficiency. There are two commonly used distribution methods in warehouses, namely "order distribution" and "wave distribution".
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Delivery to order: Refers to the process of picking and sorting goods individually for each order. This method is suitable for situations where the order quantity is small, or the type and quantity of goods in the order vary greatly. Pick-to-order can respond quickly to demand for each order, but can be less efficient because the picking process needs to be repeated multiple times.
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Wave distribution: It is to combine multiple orders into one batch according to certain rules, and then carry out unified picking and distribution. This method is suitable for situations where the order quantity is large and the goods in the order have common features. It can improve picking efficiency and reduce the walking path of pickers.
Compared with order-by-order distribution, wave distribution operations are more complex and require more advanced warehouse management system (WMS) support to optimize picking paths and improve efficiency.
2. Our solution
At present, Jiuzhang Intelligent has developed an order wave picking algorithm based on integer planning. For a large number of multi-product orders, the orders are aggregated according to SKU (Stock Keeping Unit) combinations. Based on the current order situation in the order pool, the set solution for a sufficient number of orders is calculated under the specified number of SKUs and the number of goods.
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The decision variables are:
(1) Whether to select a certain SKU combination
(2) Whether a certain SKU combination is covered in a certain wave
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The optimization goal is: maximize the number of picking orders
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Constraints to consider include:
(1) Only when a certain SKU combination is selected can it be included in a certain wave.
(2) Range limit on the number of SKUs in the combination. That is to say, in the SKU combination selected in each wave, both intensification and efficiency should be taken into consideration. For example, only one SKU should not be picked at a time, nor too many SKUs should be picked.
(3) Gather The range limit of the order quantity within the wave. That is to say, considering the capacity limit of each batch of picking, if the load is too low, cost will be wasted, and the upper limit of the capacity must not be exceeded.
In the example test, for a scale of about 122,000 orders, the algorithm can currently use about 1,100 SKU combinations in the shortest 20 seconds, covering about 95,500 orders and 1,600 SKU wave aggregation tasks, to obtain an accurate optimal solution. Table 1 shows the solution results, and Figure 1 shows the changing trend of the total algorithm running time with the size of the order processing.
Table 1. Algorithm solution results and running time
| serial number | Total orders processed | Total number of SKUs used | Total number of SKU combinations used | Total algorithm running time (seconds) |
| 1 | 98264 | 1997 | 1485 | 190.12 |
| 2 | 97588 | 1920 | 1358 | 140.17 |
| 3 | 97105 | 1840 | 1294 | 56.92 |
| 4 | 96557 | 1759 | 1230 | 36.78 |
| 5 | 95542 | 1599 | 1129 | 18.11 |
Figure 1. The changing trend of the total algorithm running time with the size of the order processed
Wave picking algorithms can be integrated with WMS in two ways.
(1) WMS organizes the query SQL, and the notification algorithm plug-in directly connects to the business database (Oralce, MSSQL, MYSQL) to query the order data, and passes the parameters: number of goods N value, wave lower limit t1, wave upper limit t2. After the calculation is completed, mark the order and notify WMS to process the wave to generate specific logic.
(2) WMS queries the order data and writes it to Redis, and notifies the algorithm plug-in to read from Redis and pass the parameters: number of items N, wave lower limit t1, wave upper limit t2. After the calculation is completed, the order data is marked with a wave mark, and WMS is notified to process the specific logic of wave generation.
Summary:E-commerce order picking is an important part of ensuring accurate delivery of orders, and its efficiency directly affects customer satisfaction and business operating costs. Although traditional order-by-order distribution is fast in response, it is inefficient; while wave distribution significantly improves picking efficiency by merging orders. Jiuzhang's intelligent order wave picking algorithm uses advanced integer programming technology to achieve rapid and accurate optimization of SKU combinations and large-scale order aggregation, solving complexity and efficiency issues in wave distribution. The algorithm's fast processing capabilities and accuracy provide strong technical support for e-commerce companies, helping to improve warehouse management efficiency and reduce operating costs. Through practical application, the algorithm has proven its effectiveness and reliability in handling large-scale order wave aggregation tasks.
Contact information:
Jiuzhang Intelligence is an algorithm company dedicated to serving society with intelligent decision-making. It has consulting and implementation teams in smart logistics, machine learning, artificial intelligence and operations optimization algorithms.
If you have any needs for optimization of order wave picking solutions, please feel free to consult us. You can contact the person in charge of Jiuzhang Intelligence to learn the details of the plan. You are also welcome to join the WeChat group below to discuss. Welcome to click on Jiuzhang Intelligent’s official website (“Click to read the original text to jump”) or follow Jiuzhang Intelligent’s official account to learn more about the intelligent decision-making product series.
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About the author:
Liu Zunzeng: Bachelor's degree in industrial engineering and master's degree in management science and engineering at Nankai University. Experience in precise algorithms and logistics optimization.
Liu Sijia: A novice in modeling and optimization algorithms who likes outdoor sports. She has relevant experience in project planning and order batch heuristic solving.
Introduction to some team members:
Wang Kejun: Industrial engineering, a student studying operations research and optimization, experience in three-dimensional packaging
Machine-translated from the Chinese original 订单波次拣选：让拣货员少走冤枉路 (published 2024-06-11). WeChat original ↗