Application of the global optimization index method to solving inverse problems of chemical kinetics

Abstract

The construction of mathematical models and the solution of inverse problems in physical chemistry are related to the minimization of difference between numerical and experimental data, which requires a multiple solution of computationally time-consuming direct problems. In order to study the mechanisms of complex chemical reactions of metal-complex catalysis and to determine their kinetic parameters, it is proposed to use the parallel index method of global optimization. The method uses the dimension reduction based on Peano curves and the information approach supplemented with the building multiple mapping ("rotated evolvement") allowing the efficient usage of hundreds of processors. A mixed local-global strategy and other modifications of the index method are used to accelerate the search procedure.