An integrated decision support framework for selecting envelope and AC systems in hot-humid climate.

This paper aims to introduce a framework that applies life cycle cost (LCC)-based optimization, life cycle assessment (LCA) and multi-criteria decision-making (MCDM) methods for the selection of optimum envelope materials and AC systems for housing projects. A total of 37 selection criteria and 28 material alternatives were first identified through a comprehensive literature review and interviews with local experts. "DesignBuilder", a computer simulation software, was used to conduct the LCC-based optimization and LCA for the identified alternatives. Furthermore, uncertainties and risk associated with the selected alternatives were computed using Monte Carlo simulation via the Crystal Ball software and Efficient Frontier analysis via the Excel Spreadsheets. The identified selection criteria were then prioritized and assigned with utility scores based on the analytical hierarchy process (AHP) and multi-attribute utility theory (MAUT) methods. Seven scenarios with different objectives were set for an existing case study. The implementation of the framework showed that when taken into account the application of multi-criteria methods, the highest saving combination of materials is selected by the framework. The validation process was carried out through conducting interviews with local experts based on the results obtained from real case project. The experts agreed that the proposed framework can be beneficial to the industry as it takes into consideration not only quantitative criteria, but also qualitative criteria that are important to owners and designers. • A framework is proposed for selecting envelope materials and AC systems for residential buildings in hot-humid climate. • Life cycle cost and environmental impact of materials and systems are analyzed. • Uncertainties and risk associated with cost elements and other parameters are analyzed. • Sensitivity analysis is conducted to identify factors affecting LCC calculations. • Quantitative and qualitative criteria that affect the selection are identified and considered. [ABSTRACT FROM AUTHOR]