Modeling fluid catalytic cracking (FCC) riser reactors is of significant importance in FCC unit control, optimization and failure detection, as well as development and design of new riser reactors. In this study, kinetic behavior of vacuum gas oil (VGO) catalytic cracking is studied by developing an 8-lump kinetic model to describe the product distribution. The feedstock and products are divided into eight lumps by reasonably simplifying reaction network, including VGO feed, diesel oil and gasoline, LPG, butylenes, propylene, ethylene, light gases, and coke. A time-on-stream non-selective catalytic activity equation is also assumed to model deactivation mechanism. Twenty-seven pairs of model kinetic parameters are estimated using two different optimization methods, namely: non-dominated sorting genetic algorithm II (NSGA-II), and chaotic particle swarm optimization (C-PSO) algorithm. Performances of both optimization methods are compared and C-PSO algorithm is selected as the superior method in terms of computation time and finding the global optimum. In the current research, based on validated estimated parameters of the preferred C-PSO method, the effects of some operating parameters on product yields distribution are investigated and discussed. This model can be used to predict the riser key products and their compositions with high degree of accuracy which may be especially useful for the conventional FCC processes with olefins production streams.