AUTOMATED LAYOUT DESIGN USING AI SYSTEMS
DOI:
https://doi.org/10.29121/shodhkosh.v6.i2s.2025.6711Keywords:
Automated Layout Design, Artificial Intelligence, Generative Adversarial Networks (Gans), Reinforcement Learning (Rl), Optimization Algorithms, Design AutomationAbstract [English]
Artificial Intelligence (AI) systems that facilitate the automated layout design are a major breakthrough in design automation in a variety of areas, including architecture, industrial design, electronics, and digital interfaces. The conventional layout design procedures are based on human skills and manual corrections that are time consuming and can be subject to subjective judgements. The more recent advances of the AI, especially in machine learning and deep learning, have allowed systems to create, analyze, and optimize the layout configurations with little human involvement. The current paper gives a detailed structure of automated layout design incorporating generative adversarial networks (GANs), reinforcement learning (RL), and optimization algorithms. The suggested methodology entails data pre-processing methods, model training processes, and analysis metrics to determine the quality of designs, efficiency, and adaptability of the design. Implementation phase shows the interaction with the currently used design tools, which shows the ability of the system to come up with layouts that are aesthetically appealing, functional, and space conscious. Its applications in industry and architecture at the VLSI/PCB layout and dynamic web interface designs. Moreover, the paper examines the possibilities of using multimodal AI systems in real-time adaptive layouts, cross-domain generalization, and scalable implementation. The proposed system will fill the gap between computational intelligence and creative design concepts to increase productivity, consistency and innovativeness in the layout creation to provide a platform in the future research field of intelligent design automation.
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Copyright (c) 2025 Danish Kundra, Aarushi Thusu, Thiagarajan C, Dr. Ramesh Sengodan, Deepak Minhas, Punam Jagdish Patil
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