Journal of Quality Engineering and Management

Abstract Decision variables aimed at improving system performance are considered one of the key issues in most industries. To this end, numerous multi-objective optimization methods have been developed in recent years to address such problems. However, most of these approaches overlook the potential correlations among objectives. In this study, an optimization approach based on a utility function framework is proposed to solve the perindopril separation problem (perindopril is a widely used and effective pharmaceutical agent for treating cardiovascular diseases and hypertension). The proposed approach not only places all objectives at a minimally acceptable level of utility from the decision maker’s (DM) perspective but also accounts for the potential correlations among the objectives and their relative importance. A comparison of the results obtained from a numerical example using the proposed method with those of existing approaches in the literature demonstrates its favorable performance.