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<p>Benchmarking is essential for assessing the effectiveness of optimization algorithms. This paper reviews standard benchmarking methods, including convergence plots, performance profiles, data profiles, and accuracy profiles, which are widely used to evaluate optimization algorithms. The principal contribution of this work is to synthesize ideas and practical suggestions from the literature, and to articulate them within a coherent and unified framework applicable to three specific contexts: constrained optimization, multi-objective optimization, and surrogate-based optimization.</p>

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A summary of benchmarking constrained, multi-objective and surrogate-assisted optimization methods

  • 期刊论文

  • 发表日期：

    2026年5月19日

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  • Charles Audet,
  • Warren Hare,
  • Christophe Tribes

摘要

Benchmarking is essential for assessing the effectiveness of optimization algorithms. This paper reviews standard benchmarking methods, including convergence plots, performance profiles, data profiles, and accuracy profiles, which are widely used to evaluate optimization algorithms. The principal contribution of this work is to synthesize ideas and practical suggestions from the literature, and to articulate them within a coherent and unified framework applicable to three specific contexts: constrained optimization, multi-objective optimization, and surrogate-based optimization.