Variable Size Population NSGA-II: VPNSGA-II

Rappa, Giovanni (2014) Variable Size Population NSGA-II: VPNSGA-II. Queensland University of Technology.

Abstract

Multi-objective optimization is an active field of research with broad applicability in aeronautics. This report details a variant of the original NSGA-II software aimed to improve the performances of such a widely used Genetic Algorithm in finding the optimal Pareto-front of a Multi-Objective optimization problem for the use of UAV and aircraft design and optimsaiton. Original NSGA-II works on a population of predetermined constant size and its computational cost to evaluate one generation is O(mn^2 ), being m the number of objective functions and n the population size. The basic idea encouraging this work is that of reduce the computational cost of the NSGA-II algorithm by making it work on a population of variable size, in order to obtain better convergence towards the Pareto-front in less time. In this work some test functions will be tested with both original NSGA-II and VPNSGA-II algorithms; each test will be timed in order to get a measure of the computational cost of each trial and the results will be compared.

Impact and interest:

Citation counts are sourced monthly from Scopus and Web of Science® citation databases.

These databases contain citations from different subsets of available publications and different time periods and thus the citation count from each is usually different. Some works are not in either database and no count is displayed. Scopus includes citations from articles published in 1996 onwards, and Web of Science® generally from 1980 onwards.

Citations counts from the Google Scholar™ indexing service can be viewed at the linked Google Scholar™ search.

Full-text downloads:

57 since deposited on 23 Nov 2015
45 in the past twelve months

Full-text downloads displays the total number of times this work’s files (e.g., a PDF) have been downloaded from QUT ePrints as well as the number of downloads in the previous 365 days. The count includes downloads for all files if a work has more than one.

ID Code: 90646
Item Type: Report
Refereed: No
Keywords: Multi-objective, optimization
Subjects: Australian and New Zealand Standard Research Classification > ENGINEERING (090000) > AEROSPACE ENGINEERING (090100) > Aircraft Performance and Flight Control Systems (090104)
Divisions: Current > Schools > School of Electrical Engineering & Computer Science
Copyright Owner: Copyright 2014 Queensland University of Technology
Deposited On: 23 Nov 2015 01:46
Last Modified: 23 Nov 2015 01:46

Export: EndNote | Dublin Core | BibTeX

Repository Staff Only: item control page