Applying of an Ontology-driven Case-based Reasoning System in Logistics

The management of logistics projects is a well known part of management science. But until now, purely quantitative and “hard” project management techniques like the critical path method and the project evaluation and review technique have been dominant. With this main stream approach, only simply structured logistics projects can normally be managed. The few attempts to use case-based reasoning (CBR) for project management failed up until now because of the difficulties when identifying those projects which contain useful, especially qualitative knowledge for the current logistics project. In this paper we present an ontology-driven casebased reasoning system (SCM Project Recommender), that can measure similarity between knowledge collections, which are written in natural language. The application is implemented using the open source CBR development framework jCOLIBRI.