102 citations · 191 across the 11 of their papers we have counts for
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cs.NE2023★ 10 cited
Stochastic Population Update Can Provably Be Helpful in Multi-Objective Evolutionary Algorithms
Chao Bian, Yawen Zhou, Miqing Li +1
Evolutionary algorithms (EAs) have been widely and successfully applied to solve multi-objective optimization problems, due to their nature of population-based search. Population u…
cs.NE2023
Non-Elitist Evolutionary Multi-Objective Optimisation: Proof-of-Principle Results
Zimin Liang, Miqing Li, Per Kristian Lehre
Elitism, which constructs the new population by preserving best solutions out of the old population and newly-generated solutions, has been a default way for population update sinc…
cs.NE2023
Multi-Objective Archiving
Miqing Li, Manuel López-Ibáñez, Xin Yao
Most multi-objective optimisation algorithms maintain an archive explicitly or implicitly during their search. Such an archive can be solely used to store high-quality solutions pr…