Many materials and chemistry scientific and/or engineering challenges require multiple objectives to be achieved simultaneously and hence there is an increased interest in framing solutions for multiobjective optimization problems (MOOPs) , . A few examples of MOOPs are reported in material science. For instance, Erps et al. demonstrated the optimization of 3D printing materials for maximal compression modulus, compression strength and toughness, while Cao et al. proposed liquid formulated products that minimize viscosity, turbidity and price and used classification to differentiate stable formulations. The implementation of MAPs for such problems is well established.