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Many-objective robust trajectory optimisation under epistemic uncertainty and imprecision

“…7 is providing an empirical lower bound on the probability of identifying the global lower expectation. The implementation of simulated annealing follows [28] by using the parameters suggested in [29] and having 5 × |N k | moves per iteration, where |N k | is the size of the neighbourhood. The taboo search implementation is completely deterministic, the point in the neighbourhood that minimises E and is not on the taboo list is always chosen.…”