Abstract Real-world optimization applications in complex systems always contain multiple factors to be optimized, which can formulated as multi-objective problems. These problems have been solved by many evolutionary algorithms like MOEA/D, NSGA-III, and KnEA. However, when the numbers of decision variables objectives increase, computation costs those mentioned will unaffordable. To reduce such...
