EURO Journal on Computational Optimization· 2026Q2
Multi-fidelity constraints in blackbox optimization
- 0citations
- Q2SCImago
- 2026year
Short summary
New algorithms IDS and DIDS leverage multi-fidelity constraint evaluations to significantly improve blackbox optimization performance, especially for costly and discontinuous problems.
AI-generated from the title and abstract; the full text is not read.
Key points
- Introduces IDS and DIDS algorithms for constrained blackbox optimization with prohibitive computational costs.
- Leverages feasibility assessments from multiple fidelity levels to reduce expensive evaluations.
- Designed for discontinuous problems where direct search methods are preferred over model-based ones.
- Demonstrates significant performance improvements when IDS/DIDS are paired with the NOMAD software.
AI-generated from the title and abstract; the full text is not read.
Abstract
This work studies constrained blackbox optimization problems that cannot be solved in reasonable time due to prohibitive computational costs. This challenge is especially prevalent in industrial applications, where blackbox evaluations are costly. However, constraints can be evaluated at various fidelities at a lower computational cost. More specifically, this work targets situations in which the infeasibility of each individual constraint can be detected at lower fidelities, and where a large discrete number of fidelities are available. Moreover, highly discontinuous problems which may fail to evaluate are considered, such that direct search methods are preferred to model-based ones. To this effect, the Interruptible Direct Search ( IDS ) and the Dynamic Interruptible Direct Search ( DIDS ) algorithms are proposed to leverage feasibility assessments from various fidelity levels to avoid high cost evaluations. The results show highly increased performances from NOMAD when it is paired with IDS or DIDS .
The authors' abstract, as published at the source. EURO Journal on Computational Optimization, 2026 · DOI ↗
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Field: Numerical Analysis
Numerical AnalysisMathematics