Experimental Results for the study "The Hypervolume Newton Method for Constrained Multi-Objective Optimization Problems"
Authors/Creators
- 1. Leiden University
- 2. Tecnologico de Monterrey, School of Engineering and Sciences
- 3. Computer Science Department, Cinvestav-IPN
Description
This repository contains the experiment results (raw data in NPZ and CSV format and Latex tables) for the study "The Hypervolume Newton Method for Constrained Multi-Objective Optimization Problems", which is accepted in Mathematical and Computational Applications journal.
The preprint version of the related paper is already online:
Wang, H.; Emmerich, M.; Deutz, A.; Hernández, V.A.S.; Schütze, O. The Hypervolume Newton Method for Constrained Multi-objective Optimization Problems. Preprints 2022, 2022110103 (doi: 10.20944/preprints202211.0103.v1).
Data description: we benchmarked three algorithms: (1) the standalone Hypervolume Netwon Method (HVN), (2) NSGA-III, and (3) the hybridization of the standalone HVN and NSGA-III on several artificial problems.
- For the standalone HVN algorithm, we tested it on three simple artificial test problems - P1, P2, and P3 (proposed in the above paper):
- 2D-example-50*.tex: problem P1
- 3D-example1*.tex: problem P2
- 3D-example2*.tex: problem P3
- For NSGA-III and the hybridization, we tested them on the equality-constrained DTLZ and Inverted DTLZ (IDTLZ) problems:
- Eq1DTLZ.*npz: DTLZ problems
- Eq1IDTLZ*.npz: IDTLZ problems
Files
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