Multi-objective Optimization Design of Low-carbon Modular Building

Abstract

In recently architectural research, there is a well-documented emphasis on energy-saving design optimization. However, there is a conspicuous deficiency in studies that address multi-objective optimization related to the long-term carbon emissions associated with building lifecycles. In this study, modular buildings in construction sites are taken as the research object, and box-type rooms are taken as the prototypical model. A set of multi-objective optimization methods for architectural design is established by series modeling tools, building performance simulation tools and NSGA-II non-dominated sorting genetic algorithm tools, combined with Python programming tools. This method is to optimize the reduction of carbon emissions, energy consumption and costs throughout the life cycle. The purpose of this investigation is to establish a methodology for assessing and optimizing architectural designs with a primary focus on carbon emissions during the design phase. The goal is to provide architects with practical insights to enhance their designs while simultaneously achieving intelligent, eco-friendly buildings.