As corporate environments and logistics have changed, warehouses have carried out various functions to increase efficiency of Supply Chain Management (SCM) /Logistics and to try to satisfy the needs of the customer.
Order-picking is the most labor intensive and time-consuming process and is increasingly important in the efficient operation of warehouses. When you consider that total volume of warehouse goods, number of orders and order frequency have increased constantly, warehouse must dispose of a larger amount of orders in the shorter order cycle times. For these reasons, order-picking significantly influences on efficiency and productivity of warehouse.
Picker-to-Stock system and Class-Based Storage (CBS) policy have received limited research attention, in spite of their dominance in practice. This paper reports on effect of order-picking performance and order batching methods with S-shape, Largest gap and Combine routing policies under random storage policy and CBS (Class-Based Storage) policy. A new batching method, based on Seed algorithms, is proposed.
In addition, this paper compares the performance of different order batching methods using a computer simulation and applying stochastic parameters, which applies diverse demand conditions that each order has particula
1. Introduction 13
1.1 Research Background 13
1.2 Motivation 16
1.3 Research Objectives and Organization 17
2. Background Review 18
2.1 Order-picking Problems 18
2.2 Order Picking Policies 21
2.3 Order Batching Problems 32
3. Proposed Order Batching Method 37
3.1 Distance metric 37
3.2 Proposed method 40
3.3 Example of Proposed method 42
4. Experiments and Results 45
4.1 Experimental Design 45
4.2 Experimental Results 58
5. Conclusion 74