The rapid expansion of e-commerce has driven traditional supermarkets to shift from manual operations to online business models in order to maintain their competitive advantage. However, the sharp increase in online orders has placed considerable pressure on operational systems constrained by limited labor and infrastructure. In this context, optimizing the order-picking process becomes crucial for improving operational efficiency and responsiveness. This study addresses this issue by modeling and optimizing the stages of order picking using algorithms such as the First-Fit Decreasing (FFD) bin packing algorithm, shortest path – Dijkstra, Nearest-Neighbor, and Reversal – for the optimal routing. These methods are employed to allocate batches and determine the shortest routes for order-picking activities. The effectiveness of the proposed approach is validated through comparative analyses with manual picking practices and simpler support methods. Furthermore, numerical experiments are presented to demonstrate the efficiency characteristics of the approach.