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RM-MEDA: A Regularity Model-Based Multiobjective Estimation of Distribution Algorithm

<12>This paper was the first to use regularity, a type of domain knowledge valid for a wide range of real-world problems in designing multi-objective evolutionary algorithms (MOEAs). The algorithm is scalable to search dimension and works efficiently with a small population, which are of great importance for solving expensive complex optimisation problems. This algorithm has been applied to design of turbine blades and vehicles. Due to this work and other papers on MOEAs, I was invited to write a column article in IEEE Computational Intelligence Magazine and to co-chair the IEEE Symposium on Multi-Criterion Decision-Making. 193 citations (Google Scholar 22/10/13)