Storage location assignment and order picking optimization in the automotive industry

Abstract

The objective of this study is to design storage assignment and order picking system using a developed mathematical model and stochastic evolutionary optimization approach in the automotive industry. It is performed in two stages. At the first stage, storage location assignment problem is solved with a class-based storage policy with the aim of minimizing warehouse transmissions by using integer programming. At the second stage, batching and routing problems are considered together to minimize travel cost in warehouse operations. Awarehouse in the automotive industry is analyzed, and an optimum solution is obtained from an integer programming model. Due to the computational time required for solving the integer programming problem, a faster genetic algorithm is also developed to form optimal batches and optimal routes for the order picker. The main advantage of the algorithm is the quick response to production orders in real-time applications. The solutions showed that the proposed approach based on genetic algorithms can be applied and integrated to any kind of warehouse layout in automotive industry.

Multi-criteria approach for products classification and their storage location assignment

“…Thus, storage policies, which assign SKUs to storage locations, generally fall into three broad categories, presented by Hausman et al, in 1976, which are class-based storage, randomized storage, and dedicated storage [21]. Class-based storage policy distributes products into classes and for each class it reserves a region within the storage area in which the products are located in any way [12,20,[22][23][24]. A dedicated storage policy reserves each storage location for a specific product and no other products can be stored in that location [6,13,25].…”

Development of Mobile Voice Picking and Cargo Tracing Systems with Internet of Things in Third-Party Logistics Warehouse Operations

“…Verschure (2014) valuated the order pick process in a warehouse and compared the effectiveness of picking process with respect to the information availability and batch size. Ene and Öztürk (2012) revealed the key factors, including time interval and storage location proximity, impacting the order picking operations in the warehouse. The study indicated that over half of the warehouse operating costs were incurred in order picking process.…”

Study on store-space assignment based on logistic AGV in e-commerce goods to person picking pattern

“…Although there are many research results of store-space assignment in the traditional person to goods picking pattern [2][3][4][5][6] , but the essential difference between the person to goods picking pattern and goods to person picking pattern, the research results of person to goods picking pattern cannot be directly applied to the store-space assignment of goods to person picking pattern. In the present literature, there are few studies on the related issues based on goods to person picking patterns.…”