AI Summary & Key Takeaways
AI InsightIn order to compare the results, First-come First-serve (FCFS) batching and S-shaped routing, which are simple and common batching and routing methods used in practice, were applied for the sample problem data sets and it was observed that the mathematical model gave better results.
📌 3 Key Takeaways
Abstract
Order picking is one of the most significant components of the warehouse management. More than 50% of the cost incurred in warehouses is due to the order picking process. Although this process has mostly been considered within the framework of economic objectives, in recent years the ergonomic perspective has become increasingly visible. Order picking studies regarding ergonomic objectives have mostly focused on low-level order picking systems, but the human factor has been ignored in high-level order picking. In order to fill this gap, this study focuses on the order picking process of a single block high-level warehouse with a special focus on human factor. For this purpose, a capacity-constrained mathematical model based on order batching and routing for the minimization of human energy expenditure is proposed. In this three-dimensional (3D) warehouse system, the distances and travel times between locations were first determined using Tchebychev formulas in order to calculate the human energy expenditure between order locations. Then, human energy matrices between order locations were created using human energy calculation formulas based on time and item weight. These matrices, which were created for three different randomly generated sample data sets, were used in the mathematical model solution and the optimum batches and routes were determined. In order to compare the results, First-come First-serve (FCFS) batching and S-shaped routing, which are simple and common batching and routing methods used in practice, were applied for the sample problem data sets and it was observed that the mathematical model gave better results.