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Evaluation of advanced Air Traffic Management §concepts is a challenging task due to the §limitations in the existing scenario generation §methodologies. Their rigorous evaluation on safety §metrics, in a variety of complex scenarios, can §provide an insight into their performance, which can §help improve upon them while developing new ones.§In this work, I propose an air traffic simulation §system, with a novel representation of airspace, §which can prototype advanced ATM concepts. I then §propose a novel evolutionary computation methodology §to algorithmically generate conflict scenarios of §increasing complexity in order to evaluate conflict §detection algorithms.§I illustrate the methodology by quantitative §evaluation of three conflict detection algorithms on §safety metrics. I then propose the use of data §mining techniques for the discovery of interesting §relationships, that may exist implicitly, in the §algorithm''s performance data.§This relationships are formed as a predictive model §for algorithm''s vulnerability which can then be §included in an ensemble that can §minimize the overall vulnerability of the system.