Despite the established superiority in finding the global as well as well-spread Pareto optimal (PO) points, the need of more numbers of function evaluations for population based evolutionary optimization techniques leads to a computationally demanding proposal. The case becomes more miserable if the function evaluations are carried out using a first principle based computationally expensive model, making the proposal not fit for online usage of the application. In this work, a Kriging based surrogate model has been proposed to replace a computationally expensive model to save execution time while performing an optimization task. A multi-objective optimization study has been carried out for the bulk vinyl acetate polymerization with long-chain branching using these surrogate as well as expensive models and Kriging PO solutions similar to those found by the first principle models are obtained with a close to 85% savings in function evaluations. © 2015 Copyright © Taylor & Francis Group, LLC.