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Paper Title: Optimization of multiple objectives in partitioning for very large scale integration circuits using evolutionary computation
Authors Name: Rajeswari.P , Dr.Theodore S Chandra
Unique Id: IJSDR2205019
Published In: Volume 7 Issue 5, May-2022
Abstract: In this paper Optimization of multiple objectives for very-large-scale integration circuits partitioning using evolutionary computation has been proposed. An efficient fitness function has been proposed that optimizes the number of interconnections as well as the delay time. Also, a two-way partitioning technique has been used in this work; so that balanced partitioning will be achieved in this work. VLSI circuit partitioning will be a Non-Polynomial (NP) hard problem. For evolutionary computation Genetic Algorithm (GA) has been used because it provides a global optimum solution for NP-hard Problems. A genetic algorithm is an evolutionary optimization technique based on the natural selection of Darwin’s Theory. Fitness value will be calculated using the fitness function; the low fitness value will be discarded for the next generation. MATLAB has been used to code the algorithm. Therefore, the proposed method might be promising to the current trends in VLSI Technology.
Keywords: Cutsize, delay time, NP-hard, VLSI, Partitioning, and GA.
Cite Article: "Optimization of multiple objectives in partitioning for very large scale integration circuits using evolutionary computation", International Journal of Science & Engineering Development Research (www.ijsdr.org), ISSN:2455-2631, Vol.7, Issue 5, page no.94 - 98, May-2022, Available :http://www.ijsdr.org/papers/IJSDR2205019.pdf
Downloads: 000223232
Publication Details: Published Paper ID: IJSDR2205019
Registration ID:200283
Published In: Volume 7 Issue 5, May-2022
DOI (Digital Object Identifier):
Page No: 94 - 98
Publisher: IJSDR | www.ijsdr.org
ISSN Number: 2455-2631

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