A dominance-based stability measure for multi-objective evolutionary algorithms

Over the years, we have been applying multi-objective evolutionary algorithms (MOEAs) to a number of real-world problems. solving multi-objective optimization problems (MOPs) in the real world faces a number of challenges including when to terminate the algorithm. This paper addresses this challenge by introducing what we call a “stability measure”. We use this measure to estimate when to stop the multi-objective evolutionary search.