Evolutionary Algorithms for Solving Multi-Objective Problems (Genetic and Evolutionary Computation)
Evolutionary Algorithms for Solving Multi-Objective Problems (Genetic and Evolutionary Computation)
Objective reduction using a feature selection technique
Proceedings of the 10th annual conference on Genetic and evolutionary computation
Study of preference relations in many-objective optimization
Proceedings of the 11th Annual conference on Genetic and evolutionary computation
Controlling dominance area of solutions and its impact on the performance of MOEAs
EMO'07 Proceedings of the 4th international conference on Evolutionary multi-criterion optimization
Pareto-, aggregation-, and indicator-based methods in many-objective optimization
EMO'07 Proceedings of the 4th international conference on Evolutionary multi-criterion optimization
Quantifying the effects of objective space dimension in evolutionary multiobjective optimization
EMO'07 Proceedings of the 4th international conference on Evolutionary multi-criterion optimization
PPSN'06 Proceedings of the 9th international conference on Parallel Problem Solving from Nature
An Investigation on Preference Order Ranking Scheme for Multiobjective Evolutionary Optimization
IEEE Transactions on Evolutionary Computation
An interactive evolutionary multi-objective optimization and decision making procedure
Applied Soft Computing
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Although Multi-objective Evolutionary Algorithms (MOEAs) have successfully been used in a wide range of real-world problems, recent studies have shown that they have scalability limitations in problems with a large number of objectives. This paper present two contributions to deal with those limitations. In one contribution we developed an objective reduction technique which can be used during the search or in the decision making process. The other contribution presents a comparison study of some preference relations designed for problems with a large number of objectives. The experimental results show that both approaches successfully deal, to a great extent, with such scalability limitations.