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In the past years meta- and matheuristic search techniques were mainly used for solving complex problems in production and logistics. The next step in heuristic search are meta-analytics methods, which is the hybridization of metaheuristics search techniques and data science or analytics. Metaheuristics or matheuristics provide a modern framework to handle complex, real-world problems also with uncertainty, data science embodies the use of prediction and information models in practical contexts. What are important design decisions for meta-analytics algorithms? How can exiting methods be adapted? What are reasonable search paradigms?

Production and Operations Management with International Focus
Faculty of Business, Economics and Statistics
University of Vienna
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