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[037] Trade-off objective functions for multi-objective optimization in simulation-based urban form generation related to energy efficiency
Keywords:Multi-objective optimization, Urban design, Energy efficiency
Objective functions to achieve energy efficient and real-estate profitable goals normally conflict each other in the urban design process. While buildings with larger floor areas become more profitable, they normally need more energy daily. To achieve these conflict goals, multi-objective optimization (MOO) models have been adopted in relevant studies because MOO is a method to find trade-off points between solutions of two or more conflicting objectives based on their interactions (Asadi et al., 2014). In particular, pareto solutions by MOO demonstrated better and diverse alternatives of energy-efficient urban design (Yang et al., 2020). Thus, this paper seeks to categorize objective functions related to energy efficiency by analyzing their characteristics and performance of trade-off relationship in MOO. According to the findings, trade-off objective functions related to energy efficiency are categorized by their intentions. The objective functions have a total of 9 intentions. Among them, the objective function of social factor with walkability, economic, and thermal environment is related to energy efficiency. Walkability impedes photovoltaic power generation because it increases the amount of shadows by making buildings narrower and taller (Moscovitz & Barath., 2022). Layouts that maximize photovoltaic power generation impair economics (Nagy et al., 2018). Minimizing cooling energy in a hot environment shortens the building length, which reduces the amount of shadows and impairs thermal comfort (Ibrahim et al., 2017). These findings are expected to be helpful to develop the energy efficient, simulation-based urban form generative design in the future.