Akademik Veri Yönetim Sistemi
Computers and Industrial Engineering, cilt.216, 2026 (SCI-Expanded, Scopus)
Warehouse management is one of the main factors that affect logistics operations. Due to the rapid growth of e-commerce, the importance of efficient warehousing has immensely increased in recent years. The main activities in every warehouse are receiving, stocking, order picking, and shipment. However, order picking contributes to the highest share of expenses with more than 50% of the total warehouse costs. Hence, most of the studies related to warehousing are focused on order picking. This study extends the joint order batching and picker routing problem to consider pre-determined levels of sturdiness to the collected items based on their physical characteristics such as weight, fragility, and shape. For this purpose, mathematical models are formulated with an objective of minimizing the traveled distance. To solve the problem, we implemented different batching strategies including First Fit Decreasing (FFD) from the bin-packing problem, an improved time-saving algorithm, and an aisle-saving algorithm. We also applied reduced variable neighborhood search (RVNS) to improve the solution quality for FFD and for the aisle-saving algorithm where a heuristic solution was developed to solve the routing problem for a batch of orders with 3 levels of sturdiness. The results show that the Improved Time-Saving algorithm provides much better solutions, achieving an average distance reduction of approximately 11.3% compared to the next-best heuristic, although it required over 264% more time on average. FFD and Aisle Saving algorithms obtained the results in a relatively short period, however Aisle Saving outperformed FFD. RVNS could notably improve the solutions obtained from the saving Algorithm by 7.8%, and while it showed numerical improvements for FFD by an average of 5.43%, these were not statistically significant.