This paper suggests an efficient optimization approach for the design of an integrated membrane bioreactor (MBR) system. Therefore, conceptual design studies to find optimal design conditions were performed with different constraints for the wastewater treatment using a mathematical modeling method. The integrated MBR system is composed of two anoxic tanks, two aerobic tanks, and one immersed membrane tank (Janus, 2013; Janus and Ulanicki, 2016). For the design of the system, the optimal process configurations, reactor volumes, and flow rates of each stream must be decided reasonably. Especially for the decision of the optimal process configurations, binary variables are generally employed as optimization decision variables for the mathematical modeling. Hence, a mixed integer nonlinear programming (MINLP) technique can be generally used to simultaneously determine the optimal design and operating conditions including process configurations. But if the MINLP problems are formulated as highly nonlinear dynamic equations, the optimal values of binary variables may sometimes be difficult to be properly decided. Thus, this paper introduces (1) the efficient optimization approach to solve the MINLP problems by parameterizing the binary variables leading to the reduction of the nonlinearity of the model, and (2) its applications to the conceptual designs of the integrated MBR system. (C) 2018 Institution of Chemical Engineers. Published by Elsevier B.V. All rights reserved.