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Multi-objective evolutionary algorithms are widely established and well developed for problems with two or three objectives. However, it is known that for many-objective optimisation, where there are typically more than three objectives, the algorithms applying Pareto optimality as a ranking metric may loose their effectiveness [1]. This paper compares(More)
— Existing evolutionary methods capable of true Many-Objective optimisation have been limited in their application: for example either initial search directions need to be specified a-priori, or the use of hypervolume limits the search in practice to less than 10 objective dimensions. This paper describes two extensions to the Multiple Single Objective(More)
A multi-objective evolutionary algorithm is used to determine the membership function distribution within the outer loop control system of a non-linear missile autopilot using lateral acceleration control. This produces a design that meets objectives related to closed loop performance such as: steady state error, overshoot, settling and rising time. The(More)