Understanding the search dynamics of multiobjective evolutionary algorithms (MOEAs) is still an open problem. This paper extends a recent network-based tool, trajectory networks (STNs), to model behavior MOEAs. Our approach uses idea decomposition, where problem transformed into several single-objective problems. We show that STNs can be used and distinguish two popular algorithms, MOEA/D NSGA-...

Nowadays, in majority of academic contexts, it has been tried to consider the highest possible level of similarities to the real world. Hence, most of the problems have complicated structures. Traditional methods for solving almost all of the mathematical and optimization problems are inefficient. As a result, meta-heuristic algorithms have been employed increasingly during recent years. In thi...