Order picking, path optimization, linear programming
Abstract
Order picking plays a crucial role in logistics and supply chain management, directly affecting efficiency, cost, and customer satisfaction. With the continuous development of e-commerce and the increasing demand for fast order fulfillment, optimizing order-picking paths has become more important than ever before. This article reviews the latest research on picking path optimization, with a focus on the application of linear programming (LP) in this field. By analyzing a large number of studies and practical cases, the effectiveness of the LP model in improving order picking was evaluated. The research results indicate that LP significantly reduces picking time and travel distance, thereby improving efficiency. However, challenges still exist, especially when adapting to complex dynamic environments, where real-time response and computational efficiency are key issues. Future research directions include combining advanced algorithms and multi-objective optimization techniques. Overall, the study emphasizes the potential of LP in improving order picking while recognizing its current limitations.
