The term "pooling problem" describes a situation in which a variety of products are blended together in a set of pools so that the combined products' qualities must meet specific standards before they can be transported downstream or to the intended audience when needed. Several models and approaches to solving the related blending & transportation process issues have been developed. We specifically recognized the difficulties caused by certain contemporary models' inability to process big dataset instances in a fair amount of time, as well as the difficulties associated with enhancing the lower bound of the relaxation solution methods utilized and optimizing product quality. Thus, we present a new hybridized reformulation (NHYB-) and its associated solution method to handle the above challenges. We also considered some Mathematical properties of the formulated model. To illustrate the flexibility, robustness and smart nature of the proposed new hybridized models (NHYB-), the simulation study to generating large instances of dataset was carried out. Again, the applications of the simulated and lifetime data from the literature to the new hybridized reformulation of standard pooling problems were carried out with a few graphical illustrations Results showed that our formulated NHYB- performed greedily over the existing ones. By implication, our model demonstrates strengths in the area of time management, optimal solution and tenacity to handle larger instances which others could not handle.