Scheduling multiple agents for picking products in a warehouse

Rubrico, Jose Ildefonso U.; Ota, Jun; Higashi, Toshimitsu; Tamura, H.

doi:10.1109/robot.2006.1641911

Cited by 11 publications

(11 citation statements)

References 9 publications

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“…Order-picking operations can be described as the following: multiple pickers are assigned the task of transferring products in a warehouse from stationary storage locations to a common loading shed or depot, where the pickers begin and end the trips in the depot [35]. As shown in Table 1, there are four main decisions in scheduling the order-picking tasks.…”

Section: Order-picking Operationmentioning

confidence: 99%

The Role of Distributed Intelligence in Warehouse Management Systems

Giannikas

McFarlane

et al. 2014

Studies in Computational Intelligence

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Abstract. 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.

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Section: Order-picking Operationmentioning

confidence: 99%

The Role of Distributed Intelligence in Warehouse Management Systems

Giannikas

McFarlane

et al. 2014

Studies in Computational Intelligence

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“…Multi-agent systems (MAS) have been studied in warehouse management systems (García et al, 2007;Kim, Graves, & Heragu, 2002;Rubrico, Ota, Higashi, & Tamura, 2006). A MAS system was proposed to control stock levels using information from inputs and outputs of a bedding company warehouse captured via RFID (García et al, 2007).…”

Section: Literature Reviewmentioning

confidence: 99%

Intelligent agent based framework to augment warehouse management systems for dynamic demand environments

Binos¹,

Bruno²,

Adamopoulos³

2021

AJIS

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Warehouses are being impacted by increasing e-commerce and omni-channel commerce. The design of current WMSs (Warehouse Management Systems) may not be suitable to this mode of operation. The golden rule of material handling is smooth product flow, but there are day-to-day operational issues that occur in the warehouse that can impact this and order fulfilment, resulting in disruptions. Standard operational process is paramount to warehouse operational control but may preclude a dynamic response to real-time operational constraints. The growth of IoT (Internet of Things) sensor and data analytics technology provide new opportunities for designing warehouse management systems that detect and reorganise around real-time constraints to mitigate the impact of day-to-day warehouse operational issues. This paper presents the design and development stage of a design science methodology of an intelligent agent framework for basic warehouse management systems. This framework is distributed, is structured around operational constraints and includes the human operator at operational and decision support levels. An agent based simulation was built to demonstrate the viability of the framework.

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“…In order to solve the picking problem in a warehouse with multiple agents, a dispatching problem has been described and shown to have a non-polynomial search space with respect to the number of agents and routes [Rubrico et al (2006)]. For dynamically changing situations, such as a high-frequency disturbance in semiconductor manufacturing, an online manufacturing rescheduling method has been presented [Cheng et al (2006)].…”

Section: Related Workmentioning

confidence: 99%