The Concept of Closed-loop Supply Chain Integration Through Agents-based System

Golińska, Paulina; Fertsch, Marek; Gómez, Jorge Marx; Oleskow, Joanna

doi:10.1007/978-3-540-71335-7_20

Cited by 14 publications

(8 citation statements)

References 13 publications

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“…In this paper an agent-based system is treated as a multi-agent system that's acts as a support tool to company existing business information system (for example ERP) and utilized their databases [2].Authors apply Jennings and Wooldridge's definition [4]: "an agent is a computer system situated in some environment, and that is capable of autonomous action in this environment in order to meet its design objectives. Agents have the following characteristic [4]: reactive, pro-activeness, social ability.…”

Section: Agent-based Systemmentioning

confidence: 99%

Agent-Based System for Planning and Coordination of Intermodal Transport

Golińska

Hajdul

2011

Advances in Intelligent and Soft Computing

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Abstract. The common access to the broadband Internet allows small and medium enterprises (SME) to joindifferent cooperation network. For over decade European Commission in order to fulfill the obligations of sustainable policy promote intermodal transportation. Despite all these efforts the utilization rate of road transportation is still growing reaching last year 76,9%. Intermodal cargo may be carried out in one and the same loading unit or vehicle, on the whole route from the sender to the consignee using the different modes of transport. Planning and coordination of intermodal transportation requires participation of different companies. The main problem still is lack of consistency between processes which are undertaken by various supply chain participants. The aim of this paper is to propose the concept of broader cooperation between intermodal transport process participants based on semantic web and multi-agent system. The application of semantic web and multi-agent system allows to improve the information exchange among different companies and better intermodal transport planning and coordination.

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Section: Agent-based Systemmentioning

confidence: 99%

Agent-Based System for Planning and Coordination of Intermodal Transport

Golińska

Hajdul

2011

Advances in Intelligent and Soft Computing

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“…They applied this system to a German newspaper producer, reporting that their system was able to cope with fluctuations in production schedules better than the central planning system that was in place. Finally, Mishra, Kumar and Chan (2012), similar to Golinska et al (2007), proposed a multi-agent architecture to handle recycling and reverse logistics issues, arguing that ABS provides an ideal solution to facilitate communication between disconnected parties in the reverse logistics chain. However, the system was not tested with real-world data.…”

Section: Automation Across Supply Chain Functionsmentioning

confidence: 99%

Will bots take over the supply chain? Revisiting agent-based supply chain automation

Mak

Brintrup

2021

International Journal of Production Economics

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Agent-based systems have the capability to fuse information from many distributed sources and create better plans faster. This feature makes agent-based systems naturally suitable to address the challenges in Supply Chain Management (SCM). Although agent-based supply chains systems have been proposed since the early 2000s; industrial uptake of them has been lagging. The reasons quoted include the immaturity of technology, a lack of interoperability with supply chain information systems, and a lack of trust in Artificial Intelligence (AI). In this paper, we revisit the agent-based supply chain and review the state of the art. We find that agent-based technology has matured, and other supporting technologies that are penetrating supply chains; are filling in gaps, leaving the concept applicable to a wider range of functions. For example, the ubiquity of IoT technology helps agents "sense" the state of affairs in a supply chain and opens up new possibilities for automation. Digital ledgers help securely transfer data between third parties, making agent-based information sharing possible, without the need to integrate Enterprise Resource Planning (ERP) systems. Learning functionality in agents enables agents to move beyond automation and towards autonomy. We note this convergence effect through conceptualising an agent-based supply chain framework, reviewing its components, and highlighting research challenges that need to be addressed in moving forward.

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“…The method helps the designer to specify and implement sustainable optimization functions in IMS providing development guidelines and modeling templates. On the other hand, in [11] it is proposed the application of agent-based systems for supply-chain synchronized production planning including management of raw materials flow as well as flow of returned by customer obsolete products and defected semi-products and products that are refused by quality control within the factory. Whereas, in [12] a multi-agent system framework to achieve coherent and consistent workflows that can meet order requirements is proposed.…”

Section: Mas and Intelligent Manufacturing Systemsmentioning

confidence: 99%