| Issue |
ITM Web Conf.
Volume 82, 2026
International Conference on NextGen Engineering Technologies and Applications for Sustainable Development (ICNEXTS’25)
|
|
|---|---|---|
| Article Number | 01007 | |
| Number of page(s) | 6 | |
| Section | Electronics Design | |
| DOI | https://doi.org/10.1051/itmconf/20268201007 | |
| Published online | 04 February 2026 | |
Optimized VLSI floor planning using genetic algorithm
1 Assistant Professor, Department of Electronics and Communication Engineering, St.Joseph’s college of Engineering, OMR, Chennai- 600119, This email address is being protected from spambots. You need JavaScript enabled to view it.
2 UG Student, Department of Electronics and Communication Engineering, St.Joseph’s college of Engineering, OMR, Chennai-600119. This email address is being protected from spambots. You need JavaScript enabled to view it.
3 UG Student, Department of Electronics and Communication Engineering , St.Joseph’s college of Engineering, OMR, Chennai-600119, This email address is being protected from spambots. You need JavaScript enabled to view it.
VLSI floorplanning is a fundamental step in physical design automation that directly impacts chip performance, power consumption, and area utilization. Classic optimization methods include SA, DMT, and PSO; their convergence speeds are rather poor, especially for large-scale designs. This paper addresses both 2D and 3D floorplanning using a Genetic Algorithm (GA). GA represents the floorplans as chromosomes and applies selection, crossover, and mutation to improve block placement iteratively. Experimental comparisons, presented in a two-row tabular format, show that the GA achieves higher efficiency in block placement, wirelength reduction, and computation time compared to SA, DMT, and PSO. The results confirm that GA is indeed one of the effective solutions for large-scale floor planning problems.
© The Authors, published by EDP Sciences, 2026
This is an Open Access article distributed under the terms of the Creative Commons Attribution License 4.0, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
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