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Dealing with Epistemic Uncertainty in Multi-objective Optimization: A Survey
- Source :
- IPMU 2018-17th International Conference on Information Processing and Management of Uncertainty in Knowledge-Based Systems, IPMU 2018-17th International Conference on Information Processing and Management of Uncertainty in Knowledge-Based Systems, Jun 2018, Cadiz, Spain. pp.260-271, Communications in Computer and Information Science ISBN: 9783319914787, IPMU (3)
- Publication Year :
- 2018
- Publisher :
- HAL CCSD, 2018.
-
Abstract
- International audience; Multi-objective optimization under epistemic uncertainty is today present as an active research area reflecting reality of many practical applications. In this paper, we try to present and discuss relevant state-of-the-art related to multi-objective optimisation with uncertain-valued objective. In fact, we give an overview of approaches that have already been proposed in this context and limitations of each one of them. We also present recent researches developed for taking into account uncertainty in the Pareto optimality aspect.
- Subjects :
- Pareto optimality
021103 operations research
Epistemic uncertainty
Management science
Computer science
0211 other engineering and technologies
Pareto principle
Context (language use)
02 engineering and technology
Multi-objective optimization
[INFO.INFO-AI]Computer Science [cs]/Artificial Intelligence [cs.AI]
0202 electrical engineering, electronic engineering, information engineering
020201 artificial intelligence & image processing
Uncertain-valued objectives
Uncertainty quantification
Subjects
Details
- Language :
- English
- ISBN :
- 978-3-319-91478-7
- ISBNs :
- 9783319914787
- Database :
- OpenAIRE
- Journal :
- IPMU 2018-17th International Conference on Information Processing and Management of Uncertainty in Knowledge-Based Systems, IPMU 2018-17th International Conference on Information Processing and Management of Uncertainty in Knowledge-Based Systems, Jun 2018, Cadiz, Spain. pp.260-271, Communications in Computer and Information Science ISBN: 9783319914787, IPMU (3)
- Accession number :
- edsair.doi.dedup.....26574cd05a6c9859ffa4fdd26f0217fe