A synthetic review of the application of multi-objective optimization models to the design of climate-responsive buildings and neighbourhoods is carried out. The review focused on the software utilized during both simulation and optimization stages, as well as on the objective functions and the design variables. The hereby work aims at identifying knowledge gaps and future trends in the research field of automation in the design of buildings. Around 140 scientific journal articles, published between 2014 and 2021, were selected from Scopus and Web of Science databases. A three-step selection process was applied to refine the search terms and to discard works investigating mechanical, structural, and seismic topics. Meta-analysis of the results highlighted that multi-objective optimization models are widely exploited for (i) enhancing building’s energy efficiency, (ii) improving thermal and (iii) visual comfort, minimizing (iv) life-cycle costs, and (v) emissions. Reviewed workflows demonstrated to be suitable for exploring different design alternatives for building envelope, systems layout, and occupancy patterns. Nonetheless, there are still some aspects that need to be further enhanced to fully enable their potential such as the ability to operate at multiple temporal and spatial scales and the possibility of exploring strategies based on sector coupling to improve a building’s energy efficiency.

The environmental impacts of sport events have been growing during the last decades, which has led to the organizing associations developing adequate countermeasures to both reduce carbon emissions due to construction and operational stages compensate for the emissions. This work aims at proposing an approach to stadiums energy enhancement that includes strategies largely recognized as effective and applicable to several building typologies (residential, commercial, academic, etc.). The selected case study is the Dacia Arena in northern Italy that has been recently refurbished and renovated. The proposed workflow has as a goal minimizing the increment of the operational emissions, caused by new heated areas in the stadium. Firstly, the energy consumption was estimated in dynamic state for Scenario 0 (current state) and Scenario 1 (refurbished state) to quantify the new plant’s energy demand. Secondly, two hypothetical system layouts were proposed and evaluated. In the first, the power for lighting, cooling and heating is supplied by a system that couples photovoltaic panels with heat pump. In the second, the same photovoltaic plant is integrated with a biomass plant and an absorption chiller. The comparison highlights the suitability of those interventions and the environmental advantages deriving from their exploitation.

This work presents a validated workflow based on an algorithm developed in Grasshopper to parametrically control the building’s shape, by maximizing the solar irradiation incident on the building envelope and minimizing the embodied emissions. The algorithm is applied to a zero-emission building concept in Nordic and Mediterranean climate zones. The algorithm enables conducting both energy and environmental assessments through Ladybug tools. The emissions embodied in materials and the solar irradiation incident on the building envelope were estimated in the early design stage. A three-steps optimization process through evolutionary solvers, such as Galapagos (one-objective) and Octopus (multi-objective), has been conducted to shape the most environmentally responsive ZEB model in both climates. The results demonstrated the replicability of the algorithm to optimize the solar irradiation by producing an increment of solar incident irradiation equal to 35% in the Mediterranean area, and to 20% in the Nordic climate. This could contribute to compensate the additional 15% of emissions due to the higher quantities of employed materials in the optimized design. The developed approach, which is based on the parametric design principles for ZEBs, represents a support instrument for designers to develop highly efficient energy solutions in the early design stages.