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October 16, 2025Open Access

Efficient search strategies for constrained multiobjective blackbox optimization

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Authors

SDSébastien Le DigabelALAntoine Lesage‐LandryLSLudovic Salomon

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Overview

This paper integrates search heuristics into the DMulti-MADS algorithm, improving efficiency in multiobjective blackbox optimization with constraints.

Key Points

  • The integration of search heuristics significantly enhances the efficiency of DMulti-MADS algorithm.
  • Numerical simulations indicate that new promising candidates improve non-dominated points found in constrained settings.
  • Quadratic models and Nelder-Mead sampling strategies serve as effective approaches to explore the decision space.
  • Computational experiments demonstrate the algorithm's performance across various engineering applications.

Cite This Study

Digabel et al. (2025) studied this question.

synapsesocial.com/papers/68f147cc724575985c3fcfb9https://doi.org/10.48550/arxiv.2504.02986
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  4. 4A Scale-Invariant Direct Multisearch Method for Mixed-Variable Multiobjective Optimization2026
  5. 5Machine Learning Algorithms for Improving Black Box Optimization Solvers2025