The optimization of building performance has gained significant attention over the past two decades, driven by the need for energy efficiency, occupant comfort, and environmental sustainability. This paper conducts a comprehensive bibliometric analysis of multi-objective optimization (MOO) for building performance, spanning research publications from 2003 to 2023. Utilizing advanced bibliometric tools such as CiteSpace, VoSviewer, and Bibliometrix, we analyzed 1604 documents from the Web of Science Core Collection to map collaborative networks, research trends, and citation patterns. The study identifies notable advancements in the integration of sophisticated optimization algorithms, including genetic algorithms and particle swarm optimization (PSO), with simulation platforms like EnergyPlus and MATLAB, while utilizing Artificial Neural Networks (ANN) for enhanced predictive capabilities. These integrations have markedly enhanced the efficiency and accuracy of optimizing key building performance metrics, including energy efficiency, thermal comfort, indoor air quality (IAQ), and cost-effectiveness. China and the United States emerged as leading contributors, with higher education institutions playing a critical role in research outputs. Key research hotspots identified include energy consumption, thermal comfort, life cycle assessment, and simulation-based optimization. The effectiveness of genetic algorithms in managing complex multi-objective problems has led to their widespread adoption. Looking forward, future research is anticipated to focus on the development of more integrated and intelligent optimization algorithms that leverage real-time data and user behavior, thus improving the adaptability and sustainability of building performance optimization. This study provides a detailed insight into the evolution and current trends in MOO research, laying a strong foundation for future investigations aimed at advancing building performance in the context of energy efficiency and environmental sustainability.

Purpose: – Economically, Malaysia has one of the fastest growing construction industries in the world; however, the necessary balance between socio-economic and ecological systems – to avoid further environmental damage – has not yet been reached by the industry. This paper aims to explore the extent of sustainable development practices (socially, environmentally and economically) in the Malaysian construction industry, focusing on the office building sector. Design/methodology/approach: – Semi-structured in-depth interviews with 30 stakeholders from various backgrounds of the Malaysian construction industry are used to explore their challenges and motivations for pursuing sustainable outcomes. Findings: – The study finds that economic issues are the first priorities among stakeholders in any decision-makings for building projects and cost becomes one of the major reasons for the slow progress in implementing sustainable practices in building projects. Socially, there is still a wide gap of knowledge and awareness on sustainability issues among stakeholders, explaining the lack of commitment in achieving sustainability. Research limitations/implications: – The sample size is only adequate to enable internal generalisation; hence, further research is required to test the generalisability of the findings in this research. Practical implications: – This paper informs the government and regulatory stakeholders, research and education sector, private sector, and clients of the building industry, where the authors currently are and the gaps that the authors have to bridge in order to make sustainability more socially acceptable and integral in the local construction industry. Originality/value: – There have been very limited studies on exploring the views from various groups of stakeholders regarding all the three components of sustainable development in the Malaysian construction industry.

This study investigates the natural ventilation provisions of residential buildings in the hot-humid climate of Putrajaya as well as the occupants’ utilization and overall satisfaction of these provisions. Five terrace house design types were selected for the study and natural ventilation (NV) provisions were identified through acquired building documents. Computer simulations were carried out on all house types to determine the ventilation rates delivered by the NV provisions. Furthermore, a total of 298 households from the selected house types were surveyed. Two house types were found not to comply with the Uniform Building By-Law (UBBL) governing NV provisions in Malaysia and those house types that complied were found to exhibit higher ventilation rates. Occupants’ level of satisfaction when utilising NV was found to be significantly related to opening sizes complying with UBBL, longer duration of opening windows, and occupants’ means of achieving comfort. This paper informs designers on the importance of complying with the required law governing NV in residential buildings. It also highlights the need for a strict effective enforcement of UBBL compliance for the purpose of building approvals.

One of the key features of green office buildings is the proper utilization of daylight in order to ensure a good visual indoor environment which can potentially increase the occupant’s productivity. However, poor daylight condition inside office buildings can occur due to improper positioning of window blinds by the occupants. Previous studies have shown that fully lowered window blinds and the use of the artificial lightings during daytime have caused many office buildings in Malaysia to have high rates of electricity consumption. Yet, the operation of window blinds is rarely considered during the calculation of building’s daylight performance in the tropics. Therefore, this paper aims to investigate the frequency of window blind operations by office occupants and the driving factors behind their window blind operations. A GBI Gold- certified office building was selected for the study. The specific objectives of this paper are, 1) to find out the correlation between window blind operations with different orientations of the building, sky conditions, time and floor levels; and 2) to gauge the occupants’ views on their window blind operations and also their satisfaction level with their visual working environment. This study used time-lapse photography to record the blinds positions and a questionnaire survey among the occupants. Results of the ANOVA and Pearson Correlation tests from the photographic analysis found a strong correlation between window blind occlusion values with the building orientations and floor levels, but not with time. The survey results revealed that most of the participants seldom adjusted their window blinds and, in most cases, excessive brightness or glare was the main issue. These results indicate that the occupants make a little effort in changing their blind positions, which may lead to a poor daylight condition. It is expected that the results of this study will serve as the initial steps in considering occupants’ behaviour in window blinds usage during the calculation process of a building’s daylight performance in order to ensure a better indoor visual environment.

This study systematically examined recent research trends in multi-objective optimization (MOO) for building performance from 2020 to 2024 and proposed a conceptual framework integrating intelligent algorithms, simulation tools, and climate adaptation strategies. A thematic analysis of 40 peer-reviewed articles was conducted using ATLAS.ti, revealing three dominant research themes: intelligent algorithms, building performance simulation techniques, and adaptive design for climate change. Quantitative analysis highlights China’s prominent contributions to the field, while the thematic analysis reveals three key findings: (1) optimization methods based on intelligent algorithms such as NSGA-II, artificial neural networks, and gradient-boosted decision trees significantly enhance computational efficiency; (2) dynamic simulation integrated with lifecycle assessment enables a more comprehensive evaluation of building performance; and (3) climate-adaptive strategies improve building resilience to future climate uncertainties. Based on these insights, the proposed framework combines these three components to achieve computational efficiency, maintain accuracy, and improve adaptability. The framework provides a systematic, data-driven approach to address trade-offs among energy efficiency, thermal comfort, and indoor air quality. Its practical value is demonstrated through applications in residential, educational, and commercial buildings across various climate zones. These case studies highlight the framework’s capability to guide high-performance, sustainable, and climate-responsive building design. Furthermore, this review identifies future research priorities, including the integration of dynamic simulation with real-time optimization, and the development of lifecycle-oriented, comprehensive evaluation systems to address emerging environmental challenges. Overall, the study contributes a holistic perspective and actionable methodology for advancing intelligent, climate-adaptive building performance optimization.