The development of autonomous greenhouses has caught the interest of many researchers and industrial considering their potential of offering an optimal environment for the growth of high-quality crops with minimum resources. Since an autonomous greenhouse is a mechatronic system, the consideration of its subsystem (e.g. heating systems) and component (e.g. actuators and sensors) interactions early in the design phase can ease the product development process. Indeed, this consideration could shorten the design process, reduce the number of redesign loops, and improve the performance of the overall mechatronic system. In the case of a greenhouse, it would lead to a higher quality of the crops and a better management of resources. In this work, the layout design of a general autonomous greenhouse is translated into an optimization problem statement while considering product-related dependencies. Then, a genetic algorithm is used to carry out the optimization of the layout design. The methodology is applied to the design of a fully autonomous greenhouse (45 cm × 30 cm × 30 cm) for the growth of plants in space. Although some objectives are conflictual, the developed algorithm proposes a compromise to obtain a near-optimal feasible layout design. The algorithm was also able to optimize the volume of components (occupied space) while considering the energy consumption and the overall mass. Their respective summed values are 2844.32 cm3, which represents 7% of the total volume, 5.86 W, and 655.8 g.

中文翻译：

---

使用产品相关依赖关系的自主温室的进化布局设计综合

自主温室的发展引起了许多研究人员和工业界的兴趣，因为它们具有为以最少资源种植优质作物提供最佳环境的潜力。由于自主温室是一个机电系统，因此在设计阶段早期考虑其子系统（例如加热系统）和组件（例如执行器和传感器）的相互作用可以简化产品开发过程。事实上，这种考虑可以缩短设计过程，减少重新设计循环的数量，并提高整个机电一体化系统的性能。在温室的情况下，它将导致更高质量的作物和更好的资源管理。在这项工作中，在考虑与产品相关的依赖关系的同时，将一般自主温室的布局设计转化为优化问题陈述。然后，利用遗传算法对版图设计进行优化。该方法应用于设计一个完全自主的温室（45 cm × 30 cm × 30 cm），用于植物在太空中的生长。尽管一些目标是相互矛盾的，但所开发的算法提出了一种折衷方案，以获得接近最优的可行布局设计。该算法还能够在考虑能耗和整体质量的同时优化组件的体积（占用空间）。它们各自的总和值为 2844.32 cm 该方法应用于设计一个完全自主的温室（45 cm × 30 cm × 30 cm），用于植物在太空中的生长。尽管一些目标是相互矛盾的，但所开发的算法提出了一种折衷方案，以获得接近最优的可行布局设计。该算法还能够在考虑能耗和整体质量的同时优化组件的体积（占用空间）。它们各自的总和值为 2844.32 cm 该方法应用于设计一个完全自主的温室（45 cm × 30 cm × 30 cm），用于植物在太空中的生长。尽管一些目标是相互矛盾的，但所开发的算法提出了一种折衷方案，以获得接近最优的可行布局设计。该算法还能够在考虑能耗和整体质量的同时优化组件的体积（占用空间）。它们各自的总和值为 2844.32 cm3，占总体积的 7%，5.86 W，655.8 g。