The use of generative design has been suggested to be a novel approach that allows designers to take advantage of computers’ computational capabilities in the exploration of design alternatives. However, the field is still sparsely explored. Therefore, this study aimed to investigate the potential use of generative design in an architectural design context. A framework was iteratively developed alongside a prototype, which was eventually demonstrated in a case study to evaluate its applicability. The development of a residential block in the northern parts of Sweden served as the case. The findings of this study further highlight the potential of generative design and its promise in an architectural context. Compared to previous studies, the presented framework is open to other generative algorithms than mainly genetic algorithms and other evaluation models than, for instance, energy performance models. The paper also presents a general technical view on the functionality of the generative design system, as well as elaborating on how to explore the solution space in a top-down fashion. This paper moves the field of generative design further by presenting a generic framework for architectural design exploration. Future research needs to focus on detailing how generative design should be applied and when in the design process.

Virtual design tools and methods can aid in creating decision bases, but it is a challenge to balance all the trade-offs between different disciplines in building design. Optimization methods are at hand, but the question is how to connect and coordinate the updating of the domain models of each discipline and centralize the product definition into one source instead of having several unconnected product definitions. Building information modelling (BIM) features the idea of centralizing the product definition to a BIM-model and creating interoperability between models from different domains and previous research reports on different applications in a number of fields within construction. Recent research features BIM-based optimization, but there is still a question of knowing how to design a BIM-based process using neutral file formats to enable multidisciplinary optimization of life-cycle energy and cost. This paper proposes a framework for neutral BIM-based multidisciplinary optimization. The framework consists of (1) a centralized master model, from which different discipline-specific domain models are generated and evaluated; and (2) an optimization algorithm controlling the optimization loop. Based on the proposed framework, a prototype was developed and used in a case study of a Swedish multifamily residential building to test the framework’s applicability in generating and optimizing multiple models based on the BIM-model. The prototype was developed to enhance the building’s sustainability performance by optimizing the trade-off between the building’s life-cycle energy (LCE) and life-cycle cost (LCC) when choosing material for the envelope. The results of the case study demonstrated the applicability of the framework and prototype in optimizing the trade-off between conflicting objectives, such as LCE and LCC, during the design process.

The construction industry has seen an increase in its complexity. This has meant an increased need for time-consuming and costly quality control. Moreover, the construction industry continues to perform detection-based quality controls with little to no focus on prevention. Quality control documentation is a source of information and data that can support the development of construction processes toward prevention. However, current documentations are ambiguous and subjective, so they remain ineffectual. A case study was performed to explore the causes of the ambiguity and subjectivity of traditional quality control documentation, and to analyze the identified project-variable procedure’s transformation into standardized or even automated documentation. Evaluating the traditional quality control’s preparation, inspection, and documentation phases highlighted unique challenges requiring tailored solutions. This study identifies the challenges of inaccurate data creation and data entry, unusable documentation, and inefficient documentation. Therefore, the usefulness of data structuring and process standardization became apparent. Hence, the study explores two solutions: a digitalized quality control system (DQCS) that ensures one accurate structured data entry method, and a centralized unit that prepares the necessary data for quality control inspections, instead of the unique preparation for each project. The results show the benefits of increased accuracy, usability, and efficiency for reliable on-site inspection and documentation.

Building developers are continuously seeking solutions to increase saleable/rentable floor area and thus the profitability of investments, especially in large/dense cities where the real estate/rental values are high and shortage of available land results in smaller building footprints. Application of passive energy efficiency measures (e.g., thick insulation in walls) not only affects the life cycle sustainability of buildings, but also the floor area and its profitability. This can affect the decisions made on the choice of measures when aiming to improve sustainability. In line with limited studies in this context, a case study is presented here in which multi-objective optimization was used to explore the impact of various passive energy efficiency measures on the life cycle sustainability when accounting for the profitability of the floor area. The building case was a high-rise apartment based on a standardized building concept situated in different locations in Sweden, namely Vindeln, Gothenburg, and Stockholm. The findings indicated that, regardless of the location, use of (1) thick cellulose coating for the roof, and (2) moderately thick expanded polystyrene for the floor, were necessary to improve the life cycle sustainability. However, the optimal wall insulation was dependent on the location; in locations with high real estate values, the scope for using thick and conventional insulations (mineral wool/cellulose) was limited due to the significant economic loss caused by floor area reductions. In general, the optimization identified optimal solutions that could save up to 1410.7 GJ energy, 23 tonnes CO₂e, and 248.4 TEUR cost from a life cycle perspective relative to the building’s initial design.