This paper describes a decision support system (DSS) built on knowledge extraction using simulation-based optimization and data mining. The paper starts with a requirements analysis based on a survey conducted with a number of industrial companies about their practices of using simulations for decision support.Based upon the analysis, a new, interactive DSS that can fulfill the industrial requirements, is proposed.The design of the cloud-based system architecture of the DSS is then described. To show the functionality and potential of the proposed DSS, an application study has been performed for the optimal design of a hypothetical but realistic flexible production cell. How important knowledge with respect to different preferences of the decision maker can be generated as rules, using the new Flexible Pattern Mining algorithm provided in the DSS, will be revealed by the results of this application study.
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