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- W2997670003 abstract "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." @default.
- W2997670003 created "2020-01-10" @default.
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- W2997670003 date "2019-12-01" @default.
- W2997670003 modified "2023-10-18" @default.
- W2997670003 title "Bioinspired Modularity in Evolutionary Computation and a Rule-Based Logic Design Solutions for Shared Office Space" @default.
- W2997670003 doi "https://doi.org/10.5151/proceedings-ecaadesigradi2019_138" @default.
- W2997670003 hasPublicationYear "2019" @default.
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