VLSI Floorplanning Using Entropy Based Intelligent Genetic Algorithm

  • Amarbir SinghEmail author
  • Leena Jain
Conference paper
Part of the Communications in Computer and Information Science book series (CCIS, volume 805)


Very Large-Scale Integrated (VLSI) floorplanning is NP-hard combinatorial optimization problem and it is vital in chip design as it determines the quality of chips. To solve this problem in an effective manner, an intelligent approach based on heuristic placement strategy and entropy based genetic algorithm is proposed in this paper called Entropy Based Intelligent Genetic Algorithm (EBIGA). In the proposed work, concept of entropy is introduced in genetic algorithm in order to resolve the problem of local optimal solution. An integer coding representation is used in this paper which makes the task of representation of modules simple. The experimental results on Microelectronics Centre of North Carolina (MCNC) and Gigascale Systems Research Centre (GSRC) benchmarks demonstrate that EBIGA can achieve the optimal and competitive solutions for both fixed-outline and outline-free floorplans.


VLSI floorplanning Entropy Genetic algorithm 



Authors are thankful to the I.K. Gujral Punjab Technical University, Jalandhar for the support and motivation for research.


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© Springer Nature Singapore Pte Ltd. 2018

Authors and Affiliations

  1. 1.I. K. Gujral Punjab Technical UniversityJalandharIndia
  2. 2.Global Institute of Management and Emerging TechnologiesAmritsarIndia

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