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

Citations

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Cited by:

  1. de Oliveira, Raphael Mazzine Barbosa & Sörensen, Kenneth & Martens, David, 2024. "A model-agnostic and data-independent tabu search algorithm to generate counterfactuals for tabular, image, and text data," European Journal of Operational Research, Elsevier, vol. 317(2), pages 286-302.
  2. Mahdi Jahangard & Ying Xie & Yuanjun Feng, 2025. "Leveraging machine learning and optimization models for enhanced seaport efficiency," Maritime Economics & Logistics, Palgrave Macmillan;International Association of Maritime Economists (IAME), vol. 27(4), pages 710-751, December.
  3. Philippe Racette & Frédéric Quesnel & Andrea Lodi & François Soumis, 2024. "Gaining insight into crew rostering instances through ML-based sequential assignment," TOP: An Official Journal of the Spanish Society of Statistics and Operations Research, Springer;Sociedad de Estadística e Investigación Operativa, vol. 32(3), pages 537-578, October.
  4. Samah Jomah & Aji S, 2024. "Meta-Heuristic Scheduling: A Review on Swarm Intelligence and Hybrid Meta-Heuristics Algorithms for Cloud Computing," SN Operations Research Forum, Springer, vol. 5(4), pages 1-42, December.
  5. Rolim, Gustavo Alencar & Tomazella, Caio Paziani & Nagano, Marcelo Seido, 2025. "On the integration of reinforcement learning and simulated annealing for the parallel batch scheduling problem with setups," European Journal of Operational Research, Elsevier, vol. 326(2), pages 220-233.
  6. Toni Pacheco & Rafael Martinelli & Anand Subramanian & Túlio A. M. Toffolo & Thibaut Vidal, 2023. "Exponential-Size Neighborhoods for the Pickup-and-Delivery Traveling Salesman Problem," Transportation Science, INFORMS, vol. 57(2), pages 463-481, March.
  7. Camur, Mustafa C. & Sharkey, Thomas C. & Vogiatzis, Chrysafis, 2023. "The stochastic pseudo-star degree centrality problem," European Journal of Operational Research, Elsevier, vol. 308(2), pages 525-539.
  8. Nguyen, Dang Viet Anh & Gunawan, Aldy & Misir, Mustafa & Hui, Lim Kwan & Vansteenwegen, Pieter, 2025. "Deep reinforcement learning for solving the stochastic e-waste collection problem," European Journal of Operational Research, Elsevier, vol. 327(1), pages 309-325.
  9. Mohammadi, Mehrdad & Dehghan, Milad & Pirayesh, Amir & Dolgui, Alexandre, 2022. "Bi‐objective optimization of a stochastic resilient vaccine distribution network in the context of the COVID‐19 pandemic," Omega, Elsevier, vol. 113(C).
  10. Martí, Rafael & Sevaux, Marc & Sörensen, Kenneth, 2025. "Fifty years of metaheuristics," European Journal of Operational Research, Elsevier, vol. 321(2), pages 345-362.
  11. Fajemisin, Adejuyigbe O. & Maragno, Donato & den Hertog, Dick, 2024. "Optimization with constraint learning: A framework and survey," European Journal of Operational Research, Elsevier, vol. 314(1), pages 1-14.
  12. Lagos, Felipe & Pereira, Jordi, 2024. "Multi-armed bandit-based hyper-heuristics for combinatorial optimization problems," European Journal of Operational Research, Elsevier, vol. 312(1), pages 70-91.
  13. Fang, Chao & Han, Zonglei & Wang, Wei & Zio, Enrico, 2023. "Routing UAVs in landslides Monitoring: A neural network heuristic for team orienteering with mandatory visits," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 175(C).
  14. Filom, Siyavash & Amiri, Amir M. & Razavi, Saiedeh, 2022. "Applications of machine learning methods in port operations – A systematic literature review," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 161(C).
  15. Haoqi Xie & Daniela Ambrosino, 2025. "Operations Research, Machine Learning, and Integrated Techniques for Decision Problems in the Seaside Area of Container Terminals," SN Operations Research Forum, Springer, vol. 6(2), pages 1-51, June.
  16. Hashemi-Petroodi, S. Ehsan & Thevenin, Simon & Kovalev, Sergey & Dolgui, Alexandre, 2023. "Markov decision process for multi-manned mixed-model assembly lines with walking workers," International Journal of Production Economics, Elsevier, vol. 255(C).
  17. Lin, Yun Hui & Yin, Xiao Feng & Tian, Qingyun, 2024. "Unlocking efficiency: End-to-end optimization learning for recurrent facility operational planning," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 189(C).
  18. Tingting Li & Wangtu Xu, 2024. "Reliable multiple allocation hub location problem under disruptions," Flexible Services and Manufacturing Journal, Springer, vol. 36(4), pages 1503-1529, December.
  19. Londe, Mariana A. & Pessoa, Luciana S. & Andrade, Carlos E. & Resende, Mauricio G.C., 2025. "Biased random-key genetic algorithms: A review," European Journal of Operational Research, Elsevier, vol. 321(1), pages 1-22.
  20. Carolina Saavedra Sueldo & Ivo Perez Colo & Mariano Paula & Sebastián A. Villar & Gerardo G. Acosta, 2025. "Simulation-based metaheuristic optimization algorithm for material handling," Journal of Intelligent Manufacturing, Springer, vol. 36(3), pages 1689-1709, March.
  21. Eduardo Guzman & Beatriz Andres & Raul Poler, 2022. "A Decision-Making Tool for Algorithm Selection Based on a Fuzzy TOPSIS Approach to Solve Replenishment, Production and Distribution Planning Problems," Mathematics, MDPI, vol. 10(9), pages 1-28, May.
  22. Laporte, Gilbert, 2024. "Fifty years of operational research: 1972–2022," European Journal of Operational Research, Elsevier, vol. 319(2), pages 347-360.
  23. Karimi-Mamaghan, Maryam & Mohammadi, Mehrdad & Pasdeloup, Bastien & Meyer, Patrick, 2023. "Learning to select operators in meta-heuristics: An integration of Q-learning into the iterated greedy algorithm for the permutation flowshop scheduling problem," European Journal of Operational Research, Elsevier, vol. 304(3), pages 1296-1330.
  24. Bootaki, Behrang & Zhang, Guoqing, 2024. "A location-production-routing problem for distributed manufacturing platforms: A neural genetic algorithm solution methodology," International Journal of Production Economics, Elsevier, vol. 275(C).
  25. Sarkar, Puja & Khanapuri, Vivekanand B. & Tiwari, Manoj Kumar, 2025. "Integration of prediction and optimization for smart stock portfolio selection," European Journal of Operational Research, Elsevier, vol. 321(1), pages 243-256.
  26. Zhou, Fangting & Lischka, Attila & Kulcsár, Balázs & Wu, Jiaming & Haghir Chehreghani, Morteza & Laporte, Gilbert, 2025. "Learning for routing: A guided review of recent developments and future directions," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 202(C).
  27. Hajar Boualamia & Abdelmoutalib Metrane & Imad Hafidi & Oumaima Mellouli, 2025. "A New Adaptation Mechanism of the ALNS Algorithm Using Reinforcement Learning," SN Operations Research Forum, Springer, vol. 6(3), pages 1-26, September.
  28. Sandra Mara Scós Venske & Carolina Paula Almeida & Myriam Regattieri Delgado, 2024. "Metaheuristics and machine learning: an approach with reinforcement learning assisting neural architecture search," Journal of Heuristics, Springer, vol. 30(3), pages 199-224, August.
  29. Iliopoulou, Christina & Makridis, Michail A. & Kouvelas, Anastasios, 2025. "Improving transit network resilience against disruptions through path redundancy," Socio-Economic Planning Sciences, Elsevier, vol. 100(C).
  30. Lu, Jiawei & Ye, Tinghan & Chen, Wenbo & Van Hentenryck, Pascal, 2025. "Boosting column generation with graph neural networks for joint rider trip planning and crew shift scheduling," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 202(C).
  31. Jens Kärcher & Herbert Meyr, 2025. "A machine learning approach for predicting the best heuristic for a large scaled Capacitated Lotsizing Problem," OR Spectrum: Quantitative Approaches in Management, Springer;Gesellschaft für Operations Research e.V., vol. 47(3), pages 889-931, September.
  32. Marcelo Becerra-Rozas & Felipe Cisternas-Caneo & Broderick Crawford & Ricardo Soto & José García & Gino Astorga & Wenceslao Palma, 2022. "Embedded Learning Approaches in the Whale Optimizer to Solve Coverage Combinatorial Problems," Mathematics, MDPI, vol. 10(23), pages 1-18, November.
  33. Suman Samanta & Deepu Philip & Shankar Chakraborty, 2025. "A Pareto communicating artificial bee colony algorithm for solving bi-objective quadratic assignment problems," OPSEARCH, Springer;Operational Research Society of India, vol. 62(4), pages 2239-2271, December.
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