Reducing bias and inefficiency in the selection algorithm
Proceedings of the Second International Conference on Genetic Algorithms on Genetic algorithms and their application
Multiobjective evolutionary algorithms: a comparative case studyand the strength Pareto approach
IEEE Transactions on Evolutionary Computation
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Applying the generalised extension principle within the area of Computing with Words (CW) typically leads to complex maximisation problems to be solved. In this paper, a GA based approach to solve such problems is presented. The problems are modelled as multi-objective maximisation problems by employing constraining conditions as additional objectives. Several methods for determining overall fitness according to the different objectives are compared, and a new promising method is introduced.