Application of Evolutionary Algorithms for Multi-objective Optimization in VLSI and Embedded Systems

M. C. Bhuvaneswari

ISBN 10: 8132219570 / ISBN 13: 9788132219576

Published by Springer, Springer Sep 2014, 2014

About this Item

This item is printed on demand - Print on Demand Titel. Neuware -This book describes how evolutionary algorithms (EA), including genetic algorithms (GA) and particle swarm optimization (PSO) can be utilized for solving multi-objective optimization problems in the area of embedded and VLSI system design. Many complex engineering optimization problems can be modelled as multi-objective formulations. This book provides an introduction to multi-objective optimization using meta-heuristic algorithms, GA and PSO and how they can be applied to problems like hardware/software partitioning in embedded systems, circuit partitioning in VLSI, design of operational amplifiers in analog VLSI, design space exploration in high-level synthesis, delay fault testing in VLSI testing and scheduling in heterogeneous distributed systems. It is shown how, in each case, the various aspects of the EA, namely its representation and operators like crossover, mutation, etc, can be separately formulated to solve these problems. This book is intended for design engineers and researchers in the field of VLSI and embedded system design. The book introduces the multi-objective GA and PSO in a simple and easily understandable way that will appeal to introductory readers.Springer-Verlag GmbH, Tiergartenstr. 17, 69121 Heidelberg 188 pp. Englisch.

Seller Inventory # 9788132219576

Bibliographic Details

• Title: Application of Evolutionary Algorithms for Multi-objective Optimization in VLSI and Embedded Systems
• Publisher: Springer, Springer Sep 2014
• Publication Date: 2014
• Language: English
• ISBN 10: 8132219570
• ISBN 13: 9788132219576
• Binding: Buch
• Condition: Neu
• Dimensions: 241W x 160H x 16D millimeters 241 millimeters width by 160 millimeters height by 16 millimeters depth
• Weight: 453 grams

About this title

Synopsis

This book describes how evolutionary algorithms (EA), including genetic algorithms (GA) and particle swarm optimization (PSO) can be utilized for solving multi-objective optimization problems in the area of embedded and VLSI system design. Many complex engineering optimization problems can be modelled as multi-objective formulations. This book provides an introduction to multi-objective optimization using meta-heuristic algorithms, GA and PSO and how they can be applied to problems like hardware/software partitioning in embedded systems, circuit partitioning in VLSI, design of operational amplifiers in analog VLSI, design space exploration in high-level synthesis, delay fault testing in VLSI testing and scheduling in heterogeneous distributed systems. It is shown how, in each case, the various aspects of the EA, namely its representation and operators like crossover, mutation, etc, can be separately formulated to solve these problems. This book is intended for design engineers and researchers in the field of VLSI and embedded system design. The book introduces the multi-objective GA and PSO in a simple and easily understandable way that will appeal to introductory readers.

About the Author

M.C. Bhuvaneswari is Associate Professor in Department of Electrical and Electronics Engineering at PSG College of Technology, Coimbatore, India. She completed her PhD in VLSI Design and Testing from Bharathiar University in 2002. She has over 20 years of research and teaching experience. Her areas of research interest include VLSI design and testing, genetic algorithms, digital signal processing, digital systems design and microprocessors. She has published her work in several journals and conferences of national and international repute. Dr. Bhuvaneswari is a Life Member of Indian Society for Technical Education, Institution of Engineers (India), Computer Society of India and System Society of India. She was honoured with the Dakshinamoorthy Award for Teaching Excellence in the year 2010.