On a Novel Genetic Algorithmic Based Methodology for Solving Nonlinearly Constrained Systems of equations and MINLP Problems

BLANCO ANÍBAL M.; SANCHEZ MABEL C.; BANDONI J. ALBERTO

Buenos Aires - Argentina

Congreso; XXII Congreso Interamericano de Ingeniería Química, V Congreso Argentino de Ingeniería Química; 2006

Asociación Argentina de Ingenieros Químicos - Confederación Interamericana de Ingenieros Químicos

The MaxMin methodology to solve nonlinear systems of equations with genetic algorithms is proposed. The developed methodology consists of an adequate reformulation of the system of equations into a nonconstrained optimization model, which can be effectively addressed with standard genetic algorithms. The proposed methodology is also applied to mixed integer nonlinear constrained optimization problems which present challenging features for deterministic and stochastic algorithms.