Optimising building life cycle performance (cost and carbon) in architectural design: a systematic review and an integrative framework

Purpose Early-stage building design optimisation research often addresses environmental impact and cost separately, despite their interdependence. Many studies apply optimisation algorithms or machine learning models to minimise either carbon emissions or material cost – but rarely both within a unified framework. This fragmented approach risks suboptimal trade-offs, where cost-efficient designs may overlook carbon impacts and vice versa. To address this gap, this study conducts a systematic literature review to examine patterns, differences and shared practices in current research. It then proposes an integrative framework for building performance optimisation that accommodates diverse cost and environmental objectives, offering clear guidance for future studies. Design/methodology/approach About 18 peer-reviewed articles (2013–2023) were identified through Scopus and Web of Science and screened using PRISMA. A dialectical systems thinking lens guided analysis across concept, methodology and value dimensions. Nine key variables were extracted in content analysis, informing the development of a step-by-step integrative framework for life cycle performance optimisation that aligns design choices with cost and environmental objectives. Findings Most studies rely on NSGA-II, MOPSO and occasionally ANN, GPR and ELM to co-optimise life-cycle cost and carbon, often excluding other performance metrics. Tools like jEPlus + EA and MOBO lack BIM integration. This study introduces a nine-step framework linking methods, standards and tools to guide future optimisation research and practice. Originality/value This study offers a novel nine-step framework that synthesises fragmented optimisation practices in early-stage building design, linking concepts, methods and values. It provides a reproducible roadmap for balancing cost and carbon, guiding future research and supporting informed design decisions.