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 approaches have been extensively studied to address such issues in the manufacturing control, this examines the possible adoption of distributed intelligence approaches in warehouse management systems.
An increasing number of companies are outsourcing their logistics, especially warehouse functions, to third party logisticsproviders. In comparison to traditional transport and warehousing services, third party logistics are more complex and encompass a broader number of functions due to the need to adapt to different customer-specific requirements. Therefore, as third party logistics continue to expand, higher performance is required from their warehouses, including tighter inventory control, shorter response time and managing a greater product variety. In particular, these improvements are subject to different customers whose requirements vary i.e. third party logistics are required to be more customer-oriented in order to be more responsive to orders with different requirements in an efficient manner.
Similar demands have occurred in manufacturing control where flexible and lean manufacturing become the mainstream requirements for many production plants because of the inability to cope with a high degree of complexity and changes corresponding to the requirements, conventional centralized approaches applied to decision making in manufacturing control can be inadequate. Therefore, a new class of approaches, which adopts the concept of distributed intelligence, have been extensively studied in recent years.