Introduces an IR2-RF operator that trains random forest on generational design-variable modifications to repair offspring in NSGA-II/III and MOEA/D, reporting improved convergence on 2-5 objective test problems without extra evaluations.
Performance comparison of nsga-ii and nsga-iii on various many-objective test problems,
1 Pith paper cite this work. Polarity classification is still indexing.
1
Pith paper citing it
fields
cs.NE 1years
2020 1verdicts
UNVERDICTED 1representative citing papers
citing papers explorer
-
Enhanced Innovized Repair Operator for Evolutionary Multi- and Many-objective Optimization
Introduces an IR2-RF operator that trains random forest on generational design-variable modifications to repair offspring in NSGA-II/III and MOEA/D, reporting improved convergence on 2-5 objective test problems without extra evaluations.