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October 20, 2025Open Access

Machine Learning Algorithms for Improving Black Box Optimization Solvers

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Authors

MKMorteza KimiaeiVKVyacheslav Kungurtsev

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Overview

This review demonstrates how machine learning and reinforcement learning improve black-box optimization methods, suggesting better scalability and adaptability.

Key Points

  • Machine learning enhances black-box optimization by providing robust and scalable solutions, making optimization more effective.
  • Key algorithms discussed include Bayesian optimization and various adaptive and learning-based optimization techniques.
  • Using machine learning for optimizing complex problems in high-dimensional and noisy environments shows promising results.
  • The review highlights significant benchmarks, including the NeurIPS 2020 BBO Challenge, to validate the proposed methods.

Cite This Study

Kimiaei et al. (2025) studied this question.

synapsesocial.com/papers/68f5fcd68d54a28a75cf1ec2https://doi.org/10.48550/arxiv.2509.25592
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