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