Multi-objective building envelope optimization for life-cycle cost and global warming potential

Decisions made in the early design stages critically determine a building's life-cycle costs and environmental impacts. Life-cycle costing (LCC) and life-cycle assessment (LCA) methods exist to analyze the economic and environmental impacts of building design alternatives; however, designers rarely use these methods because of the time and effort required for implementation. This paper presents an automated optimization method that employs a multi-objective genetic algorithm to analyze trade-offs between life-cycle cost and carbon footprint for a predefined range of building design alternatives. The design of the envelope and mechanical system for a seven-story commercial building in Atlanta, Georgia is used as a case study to compare the proposed method with conventional industry practice. Results show that the method identified design solutions that offered significant reductions in the building's life-cycle cost and carbon footprint while requiring fewer man hours than conventional approaches.