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Passive design strategies are important for achieving building sustainability given their proved influences over the building performance in both energy and indoor environmental aspects. The building layout, envelope thermophysics, building geometry and infiltration & air-tightness are major passive architectural parameters to improve the building energy efficiency. In this paper, a comprehensive literature review on simulation-based approaches to optimize passively designed buildings is conducted and corresponding research gaps are identified. Based on existing research methods, modelling experiments on a generic building are conducted to integrate robust variance-based sensitivity analyses with an early-stage design optimization process. Proposed mixed-mode ventilation and lighting dimming control algorithms are applied to the EnergyPlus model to simulate the total lighting and cooling energy demands by incorporating the related design criteria in a local green building assessment scheme. The non-dominated sorting genetic algorithm (NSGA-II) is then coupled with the modelling experiment to obtain the Pareto frontier as well as the final optimum solution. Different settings of NSGA-II are also investigated to improve the computational efficiency without jeopardizing the optimization productivity. Furthermore, the sensitivity of optimum design solutions to external environmental parameters in hot and humid areas are explored. Findings from this study will guide decision-makers through a holistic optimization process to fulfill energy-saving targets in a passively designed green building. [ABSTRACT FROM AUTHOR]