Optimal floor planning in VLSI using improved adaptive particle swarm optimization

  • S. B. Vinay KumarEmail author
  • P. V. Rao
  • Manoj Kumar Singh
Special Issue


Floor planning is necessary to design the VLSI circuit. The complete computational characteristics of the manufactured chip are evaluated by floor planning process. It is the multi-objective problem in which different objectives are fulfilled at a time. Here, a new Interactive Self-Improvement based Adaptive Particle Swarm Optimization (ISI-APSO) technique is proposed to enhance the exploration efficiency and accuracy than convolutional PSO. Within less computation time the proposed ISI-APSO technique attains best global search throughout the space. The simulation results show that the proposed ISI-APSO algorithm achieves better performance than other heuristic algorithms in exploring efficiency and speed of convergence. In order to place the whole modules and their internally connected wire lengths, the Multi-objective optimization method is utilized. Therefore the necessary layout area is minimized. Moreover, the implemented results demonstrate the importance of the proposed algorithm with respect to the robust performance.


VLSI Floor planning ISI-APSO Area Wirelength Overlap Convergence speed 



Very-large-scale integration


Integrated circuit


Interactive Self-Improvement based Adaptive Particle Optimization


Intellectual property


Input output


Non-deterministic polynomial-time hard


Simulated annealing


Ant colony optimization


Simulated annealing


Differential evolution


PSO improved Cauchy inertia weight Particle Swarm Optimization


Nonlinear inertia weight variation in Particle Swarm Optimization


Random function inertia weight Particle Swarm Optimization


Dynamic inertia weight Particle Swarm Optimization


Evolutionary based inertia weight Particle Swarm Optimization


Confidence interval


Infinite impulse response




Guided local search


Moving block sequence


Through-silicon vias


Adaptive weight PSO


Genetic algorithm



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Copyright information

© Springer-Verlag GmbH Germany, part of Springer Nature 2019

Authors and Affiliations

  • S. B. Vinay Kumar
    • 1
    Email author
  • P. V. Rao
    • 2
  • Manoj Kumar Singh
    • 3
  1. 1.School of Engineering and TechnologyBangaloreIndia
  2. 2.Vignana Bharathi Institute of TechnologyGhatkesar, HyderabadIndia
  3. 3.School of Engineering TechnologyBangaloreIndia

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