Abstract
The article describes multi-agent engine for data clustering and IF-THEN rules generation and their application to transportation logistics. The developed engine can be used for investigating customer source data, pattern discovery in batch or in real time mode and ongoing forecasting and consolidation of orders and in other cases. Engine basic architecture fits well for both batch and real time clustering. The example of data clustering and generation of IF-THEN rules for one of UK logistics operators is considered. It is shown how the extracted rules were applied to automatic schedule generation and how as a result the quality of schedules was improved. The article also describes an approach, which allows getting orders consolidation from extracted rules. Algorithm of rule search and the obtained results analysis are other points mentioned.
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Minakov, I., Rzevski, G., Skobelev, P., Volman, S. (2007). Automatic Extraction of Business Rules to Improve Quality in Planning and Consolidation in Transport Logistics Based on Multi-agent Clustering. In: Gorodetsky, V., Zhang, C., Skormin, V.A., Cao, L. (eds) Autonomous Intelligent Systems: Multi-Agents and Data Mining. AIS-ADM 2007. Lecture Notes in Computer Science(), vol 4476. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-540-72839-9_11
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DOI: https://doi.org/10.1007/978-3-540-72839-9_11
Publisher Name: Springer, Berlin, Heidelberg
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