Wenrong Lu

An algorithm for dynamic order-picking in warehouse operations

Warehousing has been traditionally viewed as a non-value-adding activity but in recent years a number of new developments have meant that supply chain logistics have become critical to profitability. This paper focuses specifically on order-picking which is a key factor affecting warehouse performance. Order picking is the operation of retrieving goods from specified storage locations based on customer orders. Today’s warehouses face challenges for greater responsiveness to customer orders that require more flexibility than conventional strategies can offer. Hence, dynamic order-picking strategies that allow for changes of pick-lists during a pick cycle have attracted attention recently. In this paper we introduce an interventionist routing algorithm for optimising the dynamic order-picking routes. The algorithm is tested using a set of simulations based on an industrial case example. The results indicate that under a range of conditions, the proposed interventionist routing algorithm can outperform both static and heuristic dynamic order-picking routing algorithms.

Intelligent logistics

HighlightsWe propose a conceptual model for customer orientation in intelligent logistics.We provide a set of structured requirements for a successful customer-oriented intelligent logistics system.We illustrate the model and structured requirements in the context using example from our current research. The role of logistics in effective supply chain management is increasingly critical, and researchers and practitioners have recently focused their attention in designing more intelligent systems to address todays challenges. In this paper, we focus on one such challenge concerning improving the role of the customer in logistics operations. In particular, we identify specific developments in the systems governing core logistics operations, which will enhance the customer experience. This paper proposes a conceptual model for customer orientation in intelligent logistics and describes a number of specific developments the authors are involved in.

Product Intelligence in Warehouse Management: A Case Study

The need for more flexible, adaptable and customer-oriented warehouse operations has been increasingly identified as an important issue by todays warehouse companies due to the rapidly changing preferences of the customers that use their services. Motivated by manufacturing and other logistics operations, in this paper we argue on the potential application of product intelligence in warehouse operations as an approach that can help warehouse companies address these issues. We discuss the opportunities of such an approach using a real example of a third-party-logistics warehouse company and we present the benefits it can bring in their warehouse management systems.

Adaptive storage location assignment for warehouses using intelligent products

Due to rapidly changing customer preferences, order-picking has become a bottleneck for the efficiency of the order fulfilment process and in turn a burden to the customer satisfaction of warehouse companies. Improved storage location assignment of newly delivered products is one effective method for improving the picking performance. However, most of the available storage policies provide static solutions that do not deal with frequent changes in order demand characteristics. This study aims to identify a potential solution by developing a distributed, adaptive strategy for the storage location assignment problem and follows the product intelligence paradigm for its implementation. The efficiency of such a strategy in real industrial systems is explored via a simulation study using data from a local e-commerce fulfilment warehouse.

The Role of Distributed Intelligence in Warehouse Management Systems

Third-party-logistics warehouses have been gaining popularity in recent years mainly due to their ability to buffer the material flow along a supply chain and consolidate the products from various suppliers, which has a major impact on supply chain efficiency. The issues and challenges in warehouse management are similar in many ways to those faced in manufacturing control, resilience and adaptability being two such issues. Since distributed intelligence (DI) approaches have been extensively studied to address such issues in manufacturing control, this paper examines the possible adoption of DI approaches in warehouse management systems (WMS). Further, the paper discusses the challenges in warehouse management and compares these challenges with the characteristics of manufacturing problems that DI approach is suited to.

New directions for warehousing data management research: Extensions to an existing review

Existing research has conducted reviews of warehousing research and has suggested potential important areas for future work. In this paper we focus on warehousing data management-related issues and augment the findings from a recent review of warehousing research to suggest new areas of future work. To determine these potential areas we visited a large, national warehousing organisation and observed their warehouses, operations, and information systems. We compared our findings against the recommendations from an academic review, and identified five new areas of important future research.