Machine learning at the service of meta-heuristics for solving combinatorial optimization problems: A state-of-the-art

Maryam Karimi-Mamaghan, Mehrdad Mohammadi, Patrick Meyer, Amir Mohammad Karimi-Mamaghan and El-Ghazali Talbi

European Journal of Operational Research, 2022, vol. 296, issue 2, 393-422

Abstract: In recent years, there has been a growing research interest in integrating machine learning techniques into meta-heuristics for solving combinatorial optimization problems. This integration aims to lead meta-heuristics toward an efficient, effective, and robust search and improve their performance in terms of solution quality, convergence rate, and robustness.

Keywords: Meta-heuristics; Machine learning; Combinatorial optimization problems; State-of-the-art (search for similar items in EconPapers)
Date: 2022
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Citations: View citations in EconPapers (20)

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Persistent link: https://EconPapers.repec.org/RePEc:eee:ejores:v:296:y:2022:i:2:p:393-422

DOI: 10.1016/j.ejor.2021.04.032

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