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Search: WFRF:(Apelkrans Mats)

  • Result 1-10 of 12
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1.
  • Apelkrans, Mats, 1939-, et al. (author)
  • Applying Multi-Agent System Technique to Production Planning in Order to Automate Decisions
  • 2009
  • In: AGENT AND MULTI-AGENT SYSTEMS. - Berlin, Heidelberg : Springer Berlin/Heidelberg. ; , s. 193-202
  • Conference paper (peer-reviewed)abstract
    • Coordinate and deliver information is vital for the financial and operational success of a company. The information is used for understanding and evaluating performance of a manufacturing company and making decisions based on incoming information. Information about orders but also parts to be purchased, assembled for the final product to be delivered, can streamline the production line to provide good quality products in the right time and to right costs at highest profit. For profit, costs are Cut by reducing storage and searching for lowest price from established suppliers and providers on web as well as handling production planning automatically. To increase profit, we apply a multi-agent technique to production planning, which can automate business decision-making for the production line. The agents handle incoming orders, the production line, and search for information about the products at the intranet and the extranet. The outcome is decisions about the production line. The multi-agent solution becomes a complement to the production planning brought about by the company's enterprise resource planning system.
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2.
  • Apelkrans, Mats, et al. (author)
  • Enterprise systems Configuration as an Information Logistics Process - A Case Study
  • 2007
  • In: Proceedings of 9th International Conference on Enterprise Information Systems. - : SciTePress. - 9789728865900 ; , s. 10-
  • Conference paper (peer-reviewed)abstract
    • In this paper, we suggest using rule-based descriptions of customer’s requirements for Enterprise Systems implementing Information Logistics. The rules are developed from the users’ requirements and inserted as schedules to the Enterprise System. The output, from testing these rules, is a list of modules and parameter setting to configure the system. By using rules, we can, at least partly, automate the configuration process for traverse the several modules and thousands parameters there are in an Enterprise System. From the list, we can select the modules and the parameters that meet the customer’s requirements. Then these selected modules and parameters are visually presented through a kind of Unified Modeling Language diagrams, to support the user investigation and then to configure the system either manually or automatically. Every attempt to match a customer’s requirement to the contents of the knowledge base within the Enterprise system can be thought of as an Information Logistics Process. The output from such a process must be examined by the user, which can give rise to a new call to the Information Logistics process. In other words the configuration work is done through a dialogue between the customer and the knowledge base of the Enterprise system.
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4.
  • Apelkrans, Mats, et al. (author)
  • Information coordination using Meta-Agents in Information Logistics Processes
  • 2008
  • In: Proceedings of Knowledge-Based and Intelligent Information & Engineering Systems. - Berlin, Heidelberg : LNCS/LNAI, Springer-Verlag. - 3540748172 - 9783540855668 ; , s. 788-798
  • Conference paper (peer-reviewed)abstract
    • In order to coordinate and deliver information in the right time and to the right place, theories from multi-agent systems and information logistics are combined. We use agents to support supply chain by searching for company specific information. Hence, there are a vast number of agents working at the Internet, simultaneously, which requires supervising agents. In this paper, we suggest using meta-agents to control the behaviour of a number of intelligent agents, where the meta-agents are working with coordination of the communication that takes place in a supply chain system. As an example, we look at a manufacturing company receiving orders on items from customers, which need to be produced. The handling of this distributed information flow can be thought of as an Information Logistics Processes and the similarities of the functioning of processes and intelligent agents’ behaviour are illuminated.
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6.
  • Apelkrans, Mats, et al. (author)
  • Visual knowledge modeling of an Information Logistics Process : A case study
  • 2005
  • In: ICICKM2005 2nd International Conference on Intellectual Capital, Knowledge Management and Organisational Learning Dubai.
  • Conference paper (peer-reviewed)abstract
    • In this paper, we present a visual knowledge modeling of an information logistics process. The model illustrates the knowledge and facts of the knowledge base, as well as the data in the database, which are needed for the handling of e-services when a case study is applied on e-invoicing. The Unified Modeling Language is used to visually describe a model for knowledge acquisition and handle the Information Logistics Process. The practical case illustrates the ideas of e-invoicing between 50 000 small and medium sized enterprises that are using the same enterprise system.
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9.
  • Håkansson, Anne, et al. (author)
  • Enterprise systems Configuration as an Information Logistics Process : A Case Study
  • 2007
  • In: Proceedings of 9th International Conference on Enterprise Information Systems, ICEIS-2007. - 9789728865900 ; , s. 212-220
  • Conference paper (peer-reviewed)abstract
    • In this paper we suggest using rule-based descriptions of customer’s requirements for Enterprise Systems implementing Information Logistics. The rules are developed from the users’ requirements and inserted as schedules to the Enterprise System. The output, from testing these rules, is a list of modules and parameter setting to configure the system. By using rules, we can, at least partly, automate the configuration process for traverse the several modules and thousands parameters there are in an Enterprise System. We can select the modules and the parameters that meet the customer’s requirements. These selected modules and parameters are visually presented through a kind of Unified Modeling Language diagrams, to support the user investigation and then to configure the system either manually or automatically. Every attempt to match a customer’s requirement to the contents of the knowledge base within the Enterprise system can be thought of as an Information Logistics Process. The output from such a process must be examined by the user, which can give rise to a new call to the Information Logistics process. In other words the configuration work is done through a dialogue between the customer and the knowledge base of the Enterprise system.
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10.
  • Håkansson, Anne, 1963-, et al. (author)
  • Information coordination using meta-agents in information logistics processes
  • 2010
  • In: Agent and Multi-agent Technology for Internet and Enterprise Systems. - Berlin/Heidelberg : Springer Berlin/Heidelberg. - 9783642135255 ; , s. 119-136
  • Book chapter (peer-reviewed)abstract
    • To be competitive, the goal for manufacturing companies is to deliver the right products at the right time with good quality. This requires good planning, optimized purchases and well functioning distribution channels. It also requires an efficient information flow in the company. One of the problems in Business Informatics is to coordinate the information flow between the manufacturing company, its customers, and its suppliers. For example, coordinating the information flow needed in a manufacturing company to fulfil their order stock. In the production process, a major issue is the double directed information flows, one from customers to company and another from company to its suppliers. This information can be about orders, requirements and production plans. Information coordination between the actors can speed up the information exchange and, hence, optimize the production cost. However, this requires a technology that can search, combine and deliver the information needed by the manufacturing company. Our approach is to combine theories from Multi Agent Systems (MAS), meta-agents and Information Logistics (IL) in order to coordinate and deliver information at the right time and to the right place at an acceptable cost.
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