Wave picking warehouse management
Currently, the market is experiencing tremendous growth in Ecommerce 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. Warehouses are adopting wave picking as an effective policy composed of item batching, loading assignment and picker routing problems.
In US, the compound annual growth rate of e-commerce is estimated to be 9.5% since 2013. In fact, of significant growth, the corresponding growth sales market draws lots of attention. Traditionally, sales orders are relatively big and precisely punctual arrivals due to the mechanism of contracts. In the field of E commerce, typical characteristics can be summarized as small order scales, large item count, unexpected irregular order arrival patterns, seasonality demand peaks, and high service level.
Warehouse management systems (WMS) cannot properly and efficiently handle managerial operation in circumstances that need additional modification and enhancement to keep running effectively. To deal with a diverse set of operations in a warehouse, most Wms apply a wave base scheme of order picking scheme.
In this system, groups of orders also referred to as wave places by customers arrive simultaneously waiting to be picked. There are several ways to increase the responding speed and operation efficiency which in turn improve the whole system. One is to minimize picking time, also can be seen as the picking make span of waves. Traditional, overall picking process basically takes up 60% of total cost in daily operations of a warehouse. In the aspect of length of time, approximately 50% of pickers’ time is spent travelling. Therefore, if the picker-routing problem can be solved effectively and efficiently, the whole operation system of a warehouse would in turn get dramatic improvement.
Total picking cost is composed of fixed picker cost and total travel cost which take up more than half of total operation management in a wave-picking warehouse.
The proposed algorithms are carefully modified to conquer several challenges caused by features of modern wave-picking warehouses like unexpected irregular order arrival patterns, high service level expectation. The measures include efficient estimation distribution generating process, effective feasible solution generation technique and valid iteration termination process
The proposed algorithms perform stable in numerical experiments, even for the large cases
The potential factors which could influence performance of the proposed algorithms are examined thoroughly in numerical experiments. The factors include algorithm parameters such as ending gap and warehouse facility parameters such as pickers’ unit travel time
Load-assignment and picker-routing problem
The proposed model involves the following decisions:
1. Number of pickers scheduled in the picking process;
2. The route each picker pass;
3. The percentage of load one picker picks. In the proposed problem, all items should be collected in one wave, so introducing travelling
The organizational structure of the order picking system can have single or multiple zones. It is based on structural and workflow strategies
Division of order picking strategies
Order picking – workflow strategies of storage and retrieval machine in high shelving warehouse
a. Order picking during inward journey only
b. Order picking during inward and return journey
c. Order picking on levels during inward and return journey
Structure of order picking time
The travel time consists of slices of time for basic route, order picking a route, and gear change, and is the biggest part of order picking time at 30 to 50 percent.
Through streamlining of the range, reducing stock/items, and removing shelf warmers, this time can be shortened:
● for static provisioning through an arrangement in line with turnover frequency, customer and component-related,
– IT route optimization; sequence of order picking;
– movement of order picker on order picking vehicles (one-dimensional);
– two-dimensional movement of order pickers (storage and retrieval machine);
– front surface reduction of storage areas (item concentration), such as continuous shelf;
– item-focused order picking, such as multi-stage process