# Best practices for comparing optimization algorithms

arXiv: https://arxiv.org/abs/1709.08242 · HTML: https://mlsanity.com/paper/1709.08242/

## Key facts

- Cited by 10 papers in the map (data through 14 Oct 2026).
- First posted on arXiv 24 Sep 2017.

## Built on by (most cited first, 10 of 10)

- [A Comparative Study of Graph Matching Algorithms in Computer Vision](https://mlsanity.com/paper/2207.00291/) (2022)
- [Transformer-Based Learned Optimization](https://mlsanity.com/paper/2212.01055/) (2022)
- [Optimization without Backpropagation](https://mlsanity.com/paper/2209.06302/) (2022)
- [A Framework for Generating Informative Benchmark Instances](https://mlsanity.com/paper/2205.14753/) (2022)
- [The Pitfalls of Benchmarking in Algorithm Selection: What We Are Getting Wrong](https://mlsanity.com/paper/2505.07750/) (2025)
- [A Statistical Analysis for Per-Instance Evaluation of Stochastic Optimizers: Avoiding Unreliable Conclusions](https://mlsanity.com/paper/2503.16589/) (2025)
- [A Framework for Discovering Optimal Solutions in Photonic Inverse Design](https://mlsanity.com/paper/2106.08419/) (2021)
- [A Study of Hybrid and Evolutionary Metaheuristics for Single Hidden Layer Feedforward Neural Network Architecture](https://mlsanity.com/paper/2506.15737/) (2025)
- [L-SR1: Learned Symmetric-Rank-One Preconditioning](https://mlsanity.com/paper/2508.12270/) (2025)
- [Linear Proposal Operators and Stochastic Search Geometry in SOMA and Differential Evolution](https://mlsanity.com/paper/2607.29228/) (2026)

## Abstract (arXiv)

Comparing, or benchmarking, of optimization algorithms is a complicated task that involves many subtle considerations to yield a fair and unbiased evaluation. In this paper, we systematically review the benchmarking process of optimization algorithms, and discuss the challenges of fair comparison. We provide suggestions for each step of the comparison process and highlight the pitfalls to avoid when evaluating the performance of optimization algorithms. We also discuss various methods of reporting the benchmarking results. Finally, some suggestions for future research are presented to improve the current benchmarking process.