The increase in global environmental concerns as well as the advancement of computational tools and methods have had significant impacts on the way in which buildings are being designed. Building professionals are increasingly expected to improve energy performance of their design. To achieve a high level of energy performance, multidisciplinary simulation-based optimization can be utilized to help designers in exploring more design alternatives and making informed decisions. Because of the high complexity in setting up a building model for multi-objective design optimization, there is a great demand of utilizing and integrating the advanced modeling and simulation technologies, including BIM, parametric modeling, cloud-based simulation, and optimization algorithms, as well as a new user interface that facilitates the setup of building parameters (decision variables) and performance fitness functions (design objectives) for automatically generating, evaluating, and optimizing multiple design options. This paper presents an integrated framework for building information modeling (BIM)-based performance optimization, BPOpt. This framework enables designers to explore design alternatives using an open-source, visual programming user interface on the top of a widely used BIM platform, to generate models of building design options, assess the environmental performance of the models through cloud-based simulation, and search for the most appropriate design alternatives. This paper details the process of the development of BPOpt and also provides a case study to show its application. The case study demonstrates the use of BPOpt in minimizing the energy consumption while maximizing the appropriate daylighting level for a residential building. Finally, strengths, limitations, current adoption by academia and industry, and future improvements of BPOpt for high-performance building design are discussed. (C) 2015 Elsevier B.V. All rights reserved.