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Evolutionary Intelligence
Published in: Evolutionary Intelligence 2/2022

09-07-2019 | Special Issue

Optimal floor planning in VLSI using improved adaptive particle swarm optimization

Authors: S. B. Vinay Kumar, P. V. Rao, Manoj Kumar Singh

Published in: Evolutionary Intelligence | Issue 2/2022

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Abstract

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.
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Metadata
Title
Optimal floor planning in VLSI using improved adaptive particle swarm optimization
Authors
S. B. Vinay Kumar
P. V. Rao
Manoj Kumar Singh
Publication date
09-07-2019
Publisher
Springer Berlin Heidelberg
Published in
Evolutionary Intelligence / Issue 2/2022
Print ISSN: 1864-5909
Electronic ISSN: 1864-5917
DOI
https://doi.org/10.1007/s12065-019-00256-z

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