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Jun 18, 2008·arXiv (Cornell University)
0 cites
Multi-agents architecture for supply chain management

Daniel Roy, Didier Anciaux, Thibaud Monteiro, Latifa Ouzizi

The purpose of this paper is to propose a new approach for the supply chain management. This approach is based on the virtual enterprise paradigm and the used of multi-agent concept. Each entity (like enterprise) is autonomous and must perform local and global goals in relation with its environment. The base component of our approach is a Virtual Enterprise Node (VEN). The supply chain is viewed as a set of tiers (corresponding to the levels of production), in which each partner of the supply chain (VEN) is in relation with several customers and suppliers. Each VEN belongs to one tier. The main customer gives global objectives (quantity, cost and delay) to the supply chain. The Mediator Agent (MA) is in charge to manage the supply chain in order to respect those objectives as global level. Those objectives are taking over to Negotiator Agent at the tier level (NAT). These two agents are only active if a perturbation occurs; otherwise information flows are only exchange between VENs. This architecture allows supply chains management which is completely transparent seen from simple enterprise of the supply chain. The used of Multi-Agent System (MAS) allows physical distribution of the decisional system. Moreover, the hierarchical organizational structure with a decentralized control guaranties, in the same time, the autonomy of each entity and the whole flexibility.

Open access
Supply Chain and Inventory Management
Scheduling and Optimization Algorithms
Collaboration in agile enterprises
Original source
Sep 23, 2006·Computers in Industry
31 cites
Multi-site coordination using a multi-agent system

Thibaud Monteiro, Daniel Roy, Didier Anciaux

A new approach of coordination of decisions in a multi site system is proposed. It is based this approach on a multi-agent concept and on the principle of distributed network of enterprises. For this purpose, each enterprise is defined as autonomous and performs simultaneously at the local and global levels. The basic component of our approach is a so-called Virtual Enterprise Node (VEN), where the enterprise network is represented as a set of tiers (like in a product breakdown structure). Within the network, each partner constitutes a VEN, which is in contact with several customers and suppliers. Exchanges between the VENs ensure the autonomy of decision, and guarantiee the consistency of information and material flows. Only two complementary VEN agents are necessary: one for external interactions, the Negotiator Agent (NA) and one for the planning of internal decisions, the Planner Agent (PA). If supply problems occur in the network, two other agents are defined: the Tier Negotiator Agent (TNA) working at the tier level only and the Supply Chain Mediator Agent (SCMA) working at the level of the enterprise network. These two agents are only active when the perturbation occurs. Otherwise, the VENs process the flow of information alone. With this new approach, managing enterprise network becomes much more transparent and looks like managing a simple enterprise in the network. The use of a Multi-Agent System (MAS) allows physical distribution of the decisional system, and procures a heterarchical organization structure with a decentralized control that guaranties the autonomy of each entity and the flexibility of the network.

Open access
2 source records
Collaboration in agile enterprises
Scheduling and Optimization Algorithms
Business Process Modeling and Analysis
Original source
Mar 9, 2006·IFIP — The International Federation for Information Processing
4 cites
The Global Automation Platform: An Agent-Based Framework for Virtual Organizations

Franco Guidi-Polanco, Claudio Cubillos, Giuseppe Menga

This work presents our agent-based architecture for the development of Global Automation Systems. These systems consist of software applications that manage all the processes in a network of enterprises, in distributed, decentralized and autonomous way. These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.

Open access
Collaboration in agile enterprises
Business Process Modeling and Analysis
Scheduling and Optimization Algorithms
Original source