On the integrity of performance comparison for evolutionary multi-objective optimisation algorithms
Authors: Wilson, K. and Rostami, S.
Journal: Advances in Intelligent Systems and Computing
Volume: 840
Pages: 3-15
ISBN: 9783319979816
ISSN: 2194-5357
DOI: 10.1007/978-3-319-97982-3_1
Abstract:This paper proposes the notion that the experimental results and performance analyses of newly developed algorithms in the field of multi-objective optimisation may not offer sufficient integrity for hypothesis testing. The reason for this is that many implementations exist of the same optimisation algorithms, and these may vary in behaviour due to the interpretation of the developer. This is demonstrated through the comparison of three implementations of the popular Non-dominated Sorting Genetic Algorithm II (NSGA-II) from well-regarded frameworks using the hypervolume indicator. The results show that of the thirty considered comparison cases, only four indicate that there was no significant difference between the performance of either implementation.
https://eprints.bournemouth.ac.uk/31060/
Source: Scopus
On the Integrity of Performance Comparison for Evolutionary Multi-objective Optimisation Algorithms
Authors: Wilson, K. and Rostami, S.
Journal: ADVANCES IN COMPUTATIONAL INTELLIGENCE SYSTEMS (UKCI)
Volume: 840
Pages: 3-15
eISSN: 2194-5365
ISBN: 978-3-319-97981-6
ISSN: 2194-5357
DOI: 10.1007/978-3-319-97982-3_1
https://eprints.bournemouth.ac.uk/31060/
Source: Web of Science (Lite)
On the Integrity of Performance Comparison for Evolutionary Multi-objective Optimisation Algorithms
Authors: Wilson, K. and Rostami, S.
Conference: UKCI 2018 : 18TH ANNUAL UK WORKSHOP ON COMPUTATIONAL INTELLIGENCE
Dates: 5-7 September 2018
https://eprints.bournemouth.ac.uk/31060/
Source: Manual
On the Integrity of Performance Comparison for Evolutionary Multi-objective Optimisation Algorithms
Authors: Wilson, K. and Rostami, S.
Conference: UKCI 2018: 18th Annual UK Workshop on Computational Intelligence
Abstract:This paper proposes the notion that the experimental results and performance analyses of newly developed algorithms in the field of multi-objective optimisation may not offer sufficient integrity for hypothesis testing. This is demonstrated through the multiple comparison of three implementations of the popular Non-dominated Sorting Genetic Algorithm II (NSGA-II) from well-regarded frameworks using the hypervolume indicator. The results show that of the thirty considered comparison cases, only four indicate that there was no significant difference between the performance of either implementation.
https://eprints.bournemouth.ac.uk/31060/
Source: BURO EPrints