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A multi-objective grouping genetic algorithm for modular design
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AI
DOI：10.1177/09544054221101743.png)
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Due to the increasingly variable market competition, product modular design is gaining in importance. This study attempts to seek a balance in three perspectives on product design: connection intensity, cost-effectiveness, and environmental protection. A multi-objective grouping genetic algorithm is adopted. Grouping genetic algorithms feature the flexible grouping and correcting mechanisms of crossover and mutation to meet the requirements of grouping, making it possible to establish a reasonable multi-objective measurement method after grouping and further offer suggestions to improve the modular design. In this study, the ceiling fan is used as an example to verify the proposed method for evaluation of the grouping method in the Matlab program. Results of the ceiling fan case verify that the proposed multi-objective algorithm is effective in modular design.
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