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FEMO (Fair Evolutionary Multiobjective Optimizer) is a population-based evolutionary algorithm for multiobjective optimization. This algorithm uses an archive of variable size that stores all non-dominated individuals. For each individual, a counter is used to count the number of times this individual has been chosen for variation. As parent individual, the individual with the lowest variation count will be chosen, ties are broken randomly. In order to keep the archive size small, a new solution is only accepted if it is not equal in all objective values to any other individual in the archive.