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A Many-objective Evolutionary Algorithm With Pareto-adaptive Reference Points−Supplementary Data: Part 2
- Citation Author(s):
- Submitted by:
- Yi Xiang
- Last updated:
- Tue, 05/17/2022 - 22:17
- DOI:
- 10.21227/9j12-ts91
- Research Article Link:
- License:
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Abstract
This is the second part of the supplementary data used in the paper "A Many-objective Evolutionary Algorithm With Pareto-adaptive Reference Points".
1. The raw IGD and HV results are obtained by setting the number of maximum function evaluations to 25,000.
2. The best and the second best results on each test problem are shaded with a dark and a light gray background, respectively.
3. In each table, the symbol $``\bullet"$ indicates that the proposed PaRP/EA significantly outperforms the peer algorithms at a 0.05 level by the Wilcoxon's rank sum test, whereas $``\circ"$ indicates the opposite, i.e. the peer algorithm shows a significant improvement over PaRP/EA. If no significant difference is detected, it will be marked by the symbol $``\ddagger"$.
