In the framework of my Ph.D. course, I developed a novel Multi-objective Evolutionary Algorithm (MOEA), namely the GeDEA-II, which features a Simplex-based crossover operator. The comparison among GeDEA-II and three modern elitist methods, on state-of-the-art multi-objective problems, clearly indicates that the performance of GeDEA-II is superior. Finally, a test case is presented, regarding the aerodynamic shape optimization of the AgustaWestland 101 helicopter left air intake.