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This paper discusses the effect of various climatic conditions that pertain to passive design measurements and their relationships with building configurations to improve indoor thermal comfort based on the different climate zones in Egypt to support Egypt’s sustainability agenda 2030. We find the most appropriate design settings that can increase the indoor thermal comfort, such as building orientation and shape. These settings can be modeled using DesignBuilder software combined with Egyptian meteorological data. This software is used accompanied by computational fluid dynamics to numerically assess the outcomes of different changes, by simulating indoor climate condition factors such as wind speed and temperature. Natural ventilation simulations were performed for four different shapes to create comprehensive dataset scenarios covering a general range of shapes and orientations. Seven scenarios were optimized to put forward a series of building bioclimatic design approaches for the different characteristic regions. The results indicated that the temperature decreased by about 3.2%, and the air velocity increased within the study domain by 200% in the best and the worst cases, respectively, of the four different shapes. The results of the study gave evidence that the configuration of buildings, direction, and wind speed are very important factors for defining the natural ventilation within these domains to support the green building concept and the sustainable design for a better lifestyle.

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The adoption of green building technology has become significant for ensuring sustainable development; it has become the main step to a sustainable future. The designs for green buildings include finding a balance between comfortable home construction and a sustainable environment. Moreover, the application of emerging technology is also used to supplement existing methods in the development of greener buildings to preserve a sustainable built environment. The main problem of this research is how to tackle the environmental parameters balance based on new techniques that are being used for green building optimization. To mitigate the cumulative effect of the constructed climate on human wellbeing and the regular ecosystem, the most popular goals for green buildings should be planned. This can be achieved by efficient use of natural resources such as energy, water, and other resources and minimizing waste. This will contribute to the security of occupant health, enhancement of work performance, emissions control, and improvement of the environment. In the construction of green buildings, several criteria that may contradict, interrelated indistinct and of qualitative and/or quantitative environment are broadened to utilize. This paper provides a detailed state of the art analysis on improving existing practices in green architecture/building using analytical hierarchy process (AHP) techniques to tackle the environmental balancing values based on optimal strategies and designs by green solutions to help make the best possible option from numerous options.

Recently, green structures turned into a huge path to an economic future. Green building outlines include finding the harmony between agreeable home living and a maintainable environment. Furthermore, the usage of modern technologies is seen as part of greener construction changes to make the urban environment more viable. This paper introduces an exhaustive state-of-art review and current practices to look for the ideal green arrangement’s models, procedures, and parameters utilizing the genetic algorithms innovations to help for settling on the most ideal choice from various options. The integrated Genetic Algorithm (GA) along with the Nondominated Sorting Genetic Algorithm strategy GA-NSGA-II is considered to be more accurate for predicting a viable future. The above methodology is widely relevant for its humility, ease of execution, and enormous durability. Besides other approaches, the GA was incorporated as well as the Neural Network (NN), Simulated Annealing (SA), Fuzzy Set theory, decision-making multicriteria, and multi-objective programming. The most fashionable methods are moderately the embedded GA-NSGA-II approaches. This paper gives an outline of the capability of GA-based MOO in supporting the advancement of methodologies of the techniques and parameters to find the best solution for the building decision-making cycle. The GA combined schemes can fulfill all the requirements for finding the optimality in the case of multi-objective problem-solving.