This study overcomes the three major difficulties experienced by the existing multi-objective evolutionary algorithms; computational cost, convergence rate, and loss of diversity of solutions, when applied to the optimisation problems with more than three objectives. The outcome comparisons clearly indicate the significance of the proposed work over numerous state-of-the-art multi-objective evolutionary algorithms.
History
Pagination
191 p.
Material type
thesis
Resource type
thesis
Language
eng
Degree type
Research doctorate
Degree name
Ph.D
Copyright notice
The author
Editor/Contributor(s)
P Lim, M Johnstone Michael, S Hanoun
Thesis faculty
Institute for Intelligent Systems Research and Innovation