A hybrid immune–evolutionary strategy algorithm for the analysis of the wide-angle X-ray diffraction curves of semicrystalline polymers

Decomposition of wide-angle X-ray diffraction curves into crystalline peaks and amorphous components is one of the most difficult nonlinear optimization problems. For this reason, the elaboration of a reliable method that provides fast unambiguous solutions remains an important and topical task. This work presents a hybrid system dedicated to this aim, combining two methods of artificial intelligence – evolution strategies and an immune algorithm – with the classical method of Rosenbrock. A combination of the mechanisms of these three methods has given a very effective and convergent algorithm that performs very well a multicriterial optimization. Tests have shown that it is faster to converge and less ambiguous than the genetic algorithm.