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Improve micro genetic algorithm for multiobjective kursawe function and low pass filter circuit design optimization

Master of Science in Microelectronic Engineering

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Bibliographic Details
Main Author: Lim, Wei Jer
Other Authors: Asral, Bahari Jambek, Dr.
Format: Thesis
Language:English
Published: Universiti Malaysia Perlis (UniMAP) 2015
Subjects:
Evolutionary computation
Computer algorithms
Algorithms
Evolutionary Algorithms (EAs)
Multiobjective Optimization Problems (MOPs)
Online Access:http://dspace.unimap.edu.my:80/xmlui/handle/123456789/72831
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spelling my.unimap-728312021-11-18T02:13:05Z Improve micro genetic algorithm for multiobjective kursawe function and low pass filter circuit design optimization Lim, Wei Jer Asral, Bahari Jambek, Dr. Evolutionary computation Computer algorithms Algorithms Evolutionary Algorithms (EAs) Multiobjective Optimization Problems (MOPs) Master of Science in Microelectronic Engineering Although Evolutionary Algorithms (EAs) have been widely implemented for solving Multiobjective Optimization Problems (MOPs), the convergence of EAs towards Pareto optimal front is still an issue of concern. In order to enhance the robustness of EAs, hybrid algorithms are commonly developed to identify better solutions for MOPs. The prime focus of this research is placed on the integration of new proposed elitism in conventional Micro Genetic Algorithm (MGA). The proposed elitism has been studied in this research to develop Improved Micro Genetic Algorithm (IMGA). In this research, Kursawe and ZDT test functions are chosen as the benchmark studies for the assessment on IMGA. The accuracy and effectiveness of IMGA are evaluated based a number of quality indicators such as generational distance and non-dominated optimal spacing. The proposed IMGA is compared with Non-dominated Sorting Genetic Algorithm II (NSGA-II), Strength Pareto Evolutionary Algorithm 2 (SPEA2), MGA and Fast Pareto Genetic Algorithm (FPGA). The assessment results show that IMGA can surpass the MGA in Kursawe test function by achieved 3.571E-4 for generational distance and 2.026E-2 for spacing. Meanwhile for ZDT benchmark, IMGA solved and suggested the optimal Pareto front for all the ZDT test functions. After having the benchmark evaluation, the proposed IMGA is applied to a practical case study on circuit design optimization. Two different circuit designs of active low pass filter that comprise of different number of input parameters are studied. 2015 2021-11-18T02:06:56Z 2021-11-18T02:06:56Z Thesis http://dspace.unimap.edu.my:80/xmlui/handle/123456789/72831 en Universiti Malaysia Perlis (UniMAP) Universiti Malaysia Perlis (UniMAP) School of Microelectronic Engineering
institution Universiti Malaysia Perlis
building UniMAP Library
collection Institutional Repository
continent Asia
country Malaysia
content_provider Universiti Malaysia Perlis
content_source UniMAP Library Digital Repository
url_provider http://dspace.unimap.edu.my/
language English
topic Evolutionary computation
Computer algorithms
Algorithms
Evolutionary Algorithms (EAs)
Multiobjective Optimization Problems (MOPs)
spellingShingle Evolutionary computation
Computer algorithms
Algorithms
Evolutionary Algorithms (EAs)
Multiobjective Optimization Problems (MOPs)
Lim, Wei Jer
Improve micro genetic algorithm for multiobjective kursawe function and low pass filter circuit design optimization
description Master of Science in Microelectronic Engineering
author2 Asral, Bahari Jambek, Dr.
author_facet Asral, Bahari Jambek, Dr.
Lim, Wei Jer
format Thesis
author Lim, Wei Jer
author_sort Lim, Wei Jer
title Improve micro genetic algorithm for multiobjective kursawe function and low pass filter circuit design optimization
title_short Improve micro genetic algorithm for multiobjective kursawe function and low pass filter circuit design optimization
title_full Improve micro genetic algorithm for multiobjective kursawe function and low pass filter circuit design optimization
title_fullStr Improve micro genetic algorithm for multiobjective kursawe function and low pass filter circuit design optimization
title_full_unstemmed Improve micro genetic algorithm for multiobjective kursawe function and low pass filter circuit design optimization
title_sort improve micro genetic algorithm for multiobjective kursawe function and low pass filter circuit design optimization
publisher Universiti Malaysia Perlis (UniMAP)
publishDate 2015
url http://dspace.unimap.edu.my:80/xmlui/handle/123456789/72831
_version_ 1724609918550409216
score 13.214268

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