Tuning of EMAS Parameters
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Having shown that EMAS approaches are effective in solving selected benchmark and real-life problems, it would be interesting to take an insight into the exact features of the most important mechanism of EMAS, i.e. the distributed selection based on existence of non-renewable resource. Such experiments could help to understand it and tune the computation based on this knowledge. The problem is not trivial, because EMAS, similar to other metaheuristics, utilises many parameters imposing on the user the setting dozens of degrees of freedom.