Please use this identifier to cite or link to this item:
|Scopus||Web of Science®||Altmetric|
|Title:||Speeding up evolutionary multi-objective optimisation through diversity-based parent selection|
|Citation:||GECCO '17: Proceedings of the 2017 Genetic and Evolutionary Computation Conference, 2017 / Bosman, P.A.N. (ed./s), pp.553-560|
|Publisher:||Association for Computing Machinery (ACM)|
|Conference Name:||Genetic and Evolutionary Computation Conference (GECCO) (15 Jul 2017 - 19 Jul 2017 : Berlin, Germany)|
|Edgar Covantes Osuna, Wanru Gao, Frank Neumann, Dirk Sudholt|
|Abstract:||Parent selection in evolutionary algorithms for multi-objective optimization is usually performed by dominance mechanisms or indicator functions that prefer non-dominated points, while the reproduction phase involves the application of diversity mechanisms or other methods to achieve a good spread of the population along the Pareto front. We propose to refine the parent selection on evolutionary multi-objective optimization with diversity-based metrics. The aim is to focus on individuals with a high diversity contribution located in poorly explored areas of the search space, so the chances of creating new non-dominated individuals are better than in highly populated areas. We show by means of rigorous runtime analysis that the use of diversity-based parent selection mechanisms in the Simple Evolutionary Multi-objective Optimiser (SEMO) and Global SEMO for the well known bi-objective functions OneMinMax and Lotz can significantly improve their performance. Our theoretical results are accompanied by additional experiments that show a correspondence between theory and empirical results.|
|Keywords:||Parent selection, evolutionary algorithms, multi-objective optimization, diversity mechanisms, runtime analysis, theory|
|Rights:||© 2017 Copyright held by the owner/author(s). Publication rights licensed to ACM.|
|Appears in Collections:||Aurora harvest 8|
Computer Science publications
Files in This Item:
There are no files associated with this item.
Items in DSpace are protected by copyright, with all rights reserved, unless otherwise indicated.