Benchmarking in Optimization: Best Practice and Open Issues

TL;DR

This survey provides comprehensive guidelines and discusses open issues in benchmarking optimization algorithms, emphasizing best practices, reproducibility, and effective analysis to improve research quality.

Contribution

It offers a set of well-structured guidelines for benchmarking in optimization, consolidating expert opinions and addressing open challenges in the field.

Findings

Identifies eight essential topics for effective benchmarking.

Highlights the importance of reproducibility and transparent reporting.

Provides recommendations for improving benchmarking practices.

Abstract

This survey compiles ideas and recommendations from more than a dozen researchers with different backgrounds and from different institutes around the world. Promoting best practice in benchmarking is its main goal. The article discusses eight essential topics in benchmarking: clearly stated goals, well-specified problems, suitable algorithms, adequate performance measures, thoughtful analysis, effective and efficient designs, comprehensible presentations, and guaranteed reproducibility. The final goal is to provide well-accepted guidelines (rules) that might be useful for authors and reviewers. As benchmarking in optimization is an active and evolving field of research this manuscript is meant to co-evolve over time by means of periodic updates.