| Project/Area Number |
17560228
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| Research Category |
Grant-in-Aid for Scientific Research (C)
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| Allocation Type | Single-year Grants |
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| Section | 一般 |
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| Research Field |
Intelligent mechanics/Mechanical systems
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| Research Institution | Kobe University |
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Principal Investigator |
KAIHARA Toshiya Kobe university, Faculty of Engineering, Professor, 工学部, 教授 (70289114)
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| Co-Investigator(Kenkyū-buntansha) |
SASHIO Kentaro Kobe university, Faculty of Engineering, Research Assistant, 工学部, 助手 (80362763)
藤井 進 神戸大学, 工学部, 教授 (00031112)
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| Project Period (FY) |
2005 – 2006
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| Project Status |
Completed (Fiscal Year 2006)
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| Budget Amount *help |
¥3,300,000 (Direct Cost: ¥3,300,000)
Fiscal Year 2006: ¥1,400,000 (Direct Cost: ¥1,400,000)
Fiscal Year 2005: ¥1,900,000 (Direct Cost: ¥1,900,000)
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| Keywords | Production management / Inventory management / Multi agent / Cost evaluation / Manufacturing simulation |
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| Research Abstract |
During the last few years the focus has shifted from factory level to enterprise level due to the increasing global presence of the companies. Supply chain management is now recognized as one of the best means by which enterprises can make instant improvements to their business strategies and operations. This in turn can lead to increase competitive advantages. Solving resource allocation problems in supply chain management with and for distributed computing systems presents particular challenges attributable to the distributed nature of the computation. In a large-scaled supply chain environment, system modules represent independent business units with conflicting and competing resource requirements, and may possess localized information relevant to their tasks. To recognize this independence, we treat the modules as agents, ascribing each of them autonomy to decide how to deploy resources under their control in service of their interests.
Market price systems constitute a well-underst
… More
ood class of mechanisms that under certain conditions provide effective decentralization of decision making with minimal communication overhead. In a market-oriented programming approach to distributed problem solving, the resource allocations for a set of computational agents is derived by computing competitive equilibrium, proposed in Walrasian economics, of an artificial economy. We define the agent activities in terms of resource required and produced, reducing an agent's decision problem to evaluate the tradeoffs of acquiring different resources. These tradeoffs are represented in terms of market prices, which define common scale of value across the various resources. To explore the use of market mechanism for the coordination of distributed planning module in supply chain management, we have developed a prototype environment for specifying and simulating computational markets with multi-echelon structure. It has been confirmed that the proposed algorithm successfully calculates. Pareto optimal solutions in the supply chain resource problem by comparing analytic approach, named fixed-point algorithm. Less
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