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Evolutionary computation is a population-based problem solver that ischaracterized by a stochastic optimization in order to solve both a singleobjective and multiple objectives. Previous evolutionary computationalresearches provided various design options and improved optimization throughbeing evolved with fitness criteria, especially when multiple design objectivesconflict with one another. In this paper, a rule-based algorithm was combinedwith the evolutionary computational process to propose an assembly logic of themodules and to improve an architectural building design in order to adapt toenvironmental changes. Two algorithms - a rule based and generative algorithmproceeded simultaneously and provided various options as well as optimization inreal time. For the experiment set-up, existing buildings were divided into eachmodule; the modules were reinterpreted and reassembled with the logic driven byEvolutionary Developmental Biology. The conclusion is that when a rule basedlogic is combined with a developmental algorithm with a modular system, it ismore efficient for the design process to be analyzed, evaluated, and optimized.The ultimate outcome provides various options in a short amount of time.