Multi objective early-stage design optimization of multifamily residential projects

Abstract

Real estate development is a multifaceted process that involves the reconstruction of the built environment to meet the needs of the community. Success depends on developers prioritizing the needs of occupants, who are directly influenced by demographic and socio-economic factors. Developers conduct market research, financial and engineering feasibility assessments, and provide detailed programs to guide the architect's design process. Optimizing architectural design, aligned with occupant profiles and their specific needs, is crucial for project success. Factors such as location, floor, daylight intake, solar radiation, and view access affect the value of each unit. To optimize early-stage architectural design, scientific analysis of these variables is essential. Numerous studies have addressed architectural optimization. Most optimization work has been done for performance-oriented purposes, such as environmental, energy, and thermal performance. However, the lack of studies that examine optimization from a user perspective and optimize designs according to the value criteria of different user types is the main motivation for this study. The aim of this study is to find a building form and plan layout that can be used in the early stages of architectural design, where criteria such as daylight, view, sun-hour, sales area, and cost are optimized according to the different expectations of different housing type users. The first phase of this study aims to find the impact of façade orientation, view, floor location, and daylight access on the value of housing units and their changes based on different housing unit types and users. This study utilized the AHP model to determine the weights of factors affecting the value of housing units, which was presented as a survey to the residents. The results were analyzed using statistical tests. According to the results, the study found that façade preference is the least important among view, daylight, and floor location preferences. park view and middle floor view are highly preferred for all apartment types, followed by south-facing view and main street view. The study indicates that residents' housing preferences and trends vary based on different unit types. Only the internal physical factors that affect the architectural form and layout were examined in this study. Many factors, such as financial, social, and environmental factors, affect the value of housing units, and those that do not affect the architectural form and layout of the building are excluded from this study. The findings of this study will enable developers to better understand the needs of home buyers and design projects that meet those needs. The second phase of this study proposes a multi-objective early-stage design optimization for a real estate development project based on the NSGA2 genetic algorithm, considering weighted user preferences for different housing types. The modelling part is employed via the platforms Rhino and Grasshopper; Wallacei is used for NSGA2, and Viktor.ai is used to deploy the app. Tested on six sample plots, the model was able to find architecturally optimized results that respond to different user expectations. While the model successfully demonstrated responsiveness to parameters, its focus on Pareto-optimal solutions limited the diversity of unit mixes generated. The model has been tested by professionals on a sample plot and is found to be important for architects and investors to generate ideas at an early stage of architectural design.