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A complementarity analysis of the COCO benchmark problems and artificially generated problems
- Source :
- GECCO Companion
- Publication Year :
- 2021
- Publisher :
- ACM, 2021.
-
Abstract
- When designing a benchmark problem set, it is important to create a set of benchmark problems that are a good generalization of the set of all possible problems. One possible way of easing this difficult task is by using artificially generated problems. In this paper, one such single-objective continuous problem generation approach is analyzed and compared with the COCO benchmark problem set, a well know problem set for benchmarking numerical optimization algorithms. Using Exploratory Landscape Analysis and Singular Value Decomposition, we show that such representations allow us to further explore the relations between the problems by applying visualization and correlation analysis techniques, with the goal of decreasing the bias in benchmark problem assessment.<br />To appear in the Proceedings of Genetic and Evolutionary Computation Conference Companion (GECCO 2021), ACM
- Subjects :
- FOS: Computer and information sciences
Set (abstract data type)
Mathematical optimization
Computer science
Generalization
Complementarity (molecular biology)
Singular value decomposition
Benchmark (computing)
Computer Science - Neural and Evolutionary Computing
Neural and Evolutionary Computing (cs.NE)
Benchmarking
Problem set
Visualization
Subjects
Details
- Database :
- OpenAIRE
- Journal :
- Proceedings of the Genetic and Evolutionary Computation Conference Companion
- Accession number :
- edsair.doi.dedup.....9adf1a9faf6d33519feb8e43e0bf0700