Automated Design of Metaheuristic Algorithms: A Survey
Abstract: Metaheuristics have gained great success in academia and practice because their search logic can be applied to any problem with available solution representation, solution quality evaluation, and certain notions of locality. Manually designing metaheuristic algorithms for solving a target problem is criticized for being laborious, error-prone, and requiring intensive specialized knowledge. This gives rise to increasing interest in automated design of metaheuristic algorithms. With computing power to fully explore potential design choices, the automated design could reach and even surpass human-level design and could make high-performance algorithms accessible to a much wider range of researchers and practitioners. This paper presents a broad picture of automated design of metaheuristic algorithms, by conducting a survey on the common grounds and representative techniques in terms of design space, design strategies, performance evaluation strategies, and target problems in this field.
Certifications: Survey Certification
Submission Length: Long submission (more than 12 pages of main content)
Previous TMLR Submission Url: https://openreview.net/forum?id=VmGjISj3WB&nesting=2&sort=date-desc
Changes Since Last Submission: We immensely appreciate the editors' and reviewers' great work and valuable comments and suggestions for the paper. As suggested by the action editor, we have double-checked the current submission to ensure that all the discussions/analyses provided in the rebuttal have been incorporated into the paper. We have also added the related works and discussions on large language models for algorithm design in the last three paragraphs of Section 4.2 of the paper.
Supplementary Material: pdf
Assigned Action Editor: ~Xi_Lin2
License: Creative Commons Attribution 4.0 International (CC BY 4.0)
Submission Number: 1725
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