A Study of Multi-Agent Based Supply Chain Modeling and Management

Um, WanSup; Lu, Huitian; Hall, Teresa

doi:10.4236/ib.2010.24043

Cited by 9 publications

(9 citation statements)

References 13 publications

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“…By implementing a manufacturing model, companies have been able to see real benefit in increased efficiencies. However, traditional manufacturing control systems are built on very rigid control architectures that cannot respond efficiently and effectively to dynamic change [16]. The process of scheduling a well can be impacted by disturbances as well.…”

Section: Review Of Related Literaturementioning

confidence: 99%

“…During these tasks, the agents must negotiate and collaborate with other agents on behalf of a human actor [16]. The MAS technology becomes the best candidate for problem solving under SCM circumstances [16]. Effective communication is imperative in SCM.…”

Section: Review Of Related Literaturementioning

confidence: 99%

“…Traditional BPM systems must be retooled where interacting agents are responsible and capable of predicting and reacting to unforeseen situations [5]. Traditional BPM is often too inflexible to meet the complex dynamic situations in distributed heterogeneous platforms [16] like those of well scheduling. In addition to supporting the processes themselves, MAS has been utilized as an effective way to realize adaptability and dynamism of process planning [21].…”

Section: Review Of Related Literaturementioning

confidence: 99%

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Modeling Well Scheduling as a Virtual Enterprise with Intelligent Agents

Lange

Lin

2014

2014 IEEE 17th International Conference on Computational Science and Engineering

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In today's intensive competitive environment in the oil and gas industry, it is important to increase efficiency in production through resource management and well scheduling (resource scheduling, for short). However, resource scheduling has been a challenge for oil and gas companies for many years because it is influenced by a number of factors including environment, regulations, stakeholders, finances, the market, and approaches to determine and plan daily schedulable tasks This paper proposes a new approach to modeling well scheduling processes in oil and gas industry using the notion of virtual enterprise with intelligent agents and contract net protocol in multiagent systems technologies. This model will lead to a flexible well scheduling application that will assist in the scheduling of resources across the well lifecycle. We show the effectiveness of the approach by implementing an experimental system and giving a case study.

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Section: Review Of Related Literaturementioning

confidence: 99%

Section: Review Of Related Literaturementioning

confidence: 99%

Section: Review Of Related Literaturementioning

confidence: 99%

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Modeling Well Scheduling as a Virtual Enterprise with Intelligent Agents

Lange

Lin

2014

2014 IEEE 17th International Conference on Computational Science and Engineering

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“…A supply chain can produce products for multiple markets. Likewise, an individual company is likely to receive only limited visibility of the supply chain structure, which makes it difficult to make future demand estimations, because the shape of demand propagation through the supply chain depends on the capabilities and strategies of companies along the path from the markets to the company [4].…”

Section: Related Work and Directionsmentioning

confidence: 99%

“…One company in one directional way cannot govern the collaborations in supply chains, coordination of companies through autonomous participation is needed. Here, agent technology is regarded as one of the best candidates for supply chain management for the above reasons [4].…”

Section: Introductionmentioning

confidence: 99%

Multiagent based open source for supply chain management using JADE

John¹,

Balakrishnan

2014

International Conference on Information Communication and Embedded Systems (ICICES2014)

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Supply chain management (SCM) is a verychallenging problem that us leveraging the e-commerce explosion. Today's supply chains are essentially static, because they rely on long-term relationship among key trading partners. Dynamic practices are vital because they offer better matches between suppliers and customers as market conditions change. Multi-agent systems (MAS) offer new perspectives compared to conventional, centrally organized architectures in the scope of supply chain management (SCM). Their structure inherently meets the requirements of decentralized supply chains, whereas conventional SCM systems are often restricted in terms of dynamic behavior, handling severe disturbances at supplier sites as well as dealing with highly customized or complex products. Since necessary data are not available within the whole supply chain, an integrated approach to production planning and control taking into account all the partners involved is not feasible. In this paper a MAS architecture integrating various intelligent agent systems is presented to address the problem.

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