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Hyper-heuristics: a survey of the state of the art

Citations

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Cited by:

  1. Folarin B. Oyebolu & Jeroen Lidth de Jeude & Cyrus Siganporia & Suzanne S. Farid & Richard Allmendinger & Juergen Branke, 2017. "A new lot sizing and scheduling heuristic for multi-site biopharmaceutical production," Journal of Heuristics, Springer, vol. 23(4), pages 231-256, August.
  2. Ahmed, Leena & Mumford, Christine & Kheiri, Ahmed, 2019. "Solving urban transit route design problem using selection hyper-heuristics," European Journal of Operational Research, Elsevier, vol. 274(2), pages 545-559.
  3. Pandian Vasant & Utku Kose & Junzo Watada, 2017. "Metaheuristic Techniques in Enhancing the Efficiency and Performance of Thermo-Electric Cooling Devices," Energies, MDPI, vol. 10(11), pages 1-50, October.
  4. Belinda Spratt & Erhan Kozan, 2021. "An integrated rolling horizon approach to increase operating theatre efficiency," Journal of Scheduling, Springer, vol. 24(1), pages 3-25, February.
  5. Yanwei Zhao & Longlong Leng & Chunmiao Zhang, 2021. "A novel framework of hyper-heuristic approach and its application in location-routing problem with simultaneous pickup and delivery," Operational Research, Springer, vol. 21(2), pages 1299-1332, June.
  6. Ahmed Kheiri & Alina G. Dragomir & David Mueller & Joaquim Gromicho & Caroline Jagtenberg & Jelke J. Hoorn, 2019. "Tackling a VRP challenge to redistribute scarce equipment within time windows using metaheuristic algorithms," EURO Journal on Transportation and Logistics, Springer;EURO - The Association of European Operational Research Societies, vol. 8(5), pages 561-595, December.
  7. Wilson, Dennis & Rodrigues, Silvio & Segura, Carlos & Loshchilov, Ilya & Hutter, Frank & Buenfil, Guillermo López & Kheiri, Ahmed & Keedwell, Ed & Ocampo-Pineda, Mario & Özcan, Ender & Peña, Sergio Iv, 2018. "Evolutionary computation for wind farm layout optimization," Renewable Energy, Elsevier, vol. 126(C), pages 681-691.
  8. Andrzej Kozik, 2017. "Handling precedence constraints in scheduling problems by the sequence pair representation," Journal of Combinatorial Optimization, Springer, vol. 33(2), pages 445-472, February.
  9. Lenin Kanagasabai, 2022. "Real power loss reduction by Q-learning and hyper-heuristic method," International Journal of System Assurance Engineering and Management, Springer;The Society for Reliability, Engineering Quality and Operations Management (SREQOM),India, and Division of Operation and Maintenance, Lulea University of Technology, Sweden, vol. 13(4), pages 1607-1622, August.
  10. Soria-Alcaraz, Jorge A. & Ochoa, Gabriela & Sotelo-Figeroa, Marco A. & Burke, Edmund K., 2017. "A methodology for determining an effective subset of heuristics in selection hyper-heuristics," European Journal of Operational Research, Elsevier, vol. 260(3), pages 972-983.
  11. Fabio Caraffini & Giovanni Iacca, 2020. "The SOS Platform: Designing, Tuning and Statistically Benchmarking Optimisation Algorithms," Mathematics, MDPI, vol. 8(5), pages 1-31, May.
  12. Chen, Yujie & Cowling, Peter & Polack, Fiona & Remde, Stephen & Mourdjis, Philip, 2017. "Dynamic optimisation of preventative and corrective maintenance schedules for a large scale urban drainage system," European Journal of Operational Research, Elsevier, vol. 257(2), pages 494-510.
  13. Yannik Zeiträg & José Rui Figueira, 2023. "Automatically evolving preference-based dispatching rules for multi-objective job shop scheduling," Journal of Scheduling, Springer, vol. 26(3), pages 289-314, June.
  14. Venkatesh Pandiri & Alok Singh, 2020. "Two multi-start heuristics for the k-traveling salesman problem," OPSEARCH, Springer;Operational Research Society of India, vol. 57(4), pages 1164-1204, December.
  15. Bongiovanni, Claudia & Kaspi, Mor & Cordeau, Jean-François & Geroliminis, Nikolas, 2022. "A machine learning-driven two-phase metaheuristic for autonomous ridesharing operations," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 165(C).
  16. Franck Butelle & Laurent Alfandari & Camille Coti & Lucian Finta & Lucas Létocart & Gérard Plateau & Frédéric Roupin & Antoine Rozenknop & Roberto Wolfler Calvo, 2016. "Fast machine reassignment," Annals of Operations Research, Springer, vol. 242(1), pages 133-160, July.
  17. José García & Gino Astorga & Víctor Yepes, 2021. "An Analysis of a KNN Perturbation Operator: An Application to the Binarization of Continuous Metaheuristics," Mathematics, MDPI, vol. 9(3), pages 1-20, January.
  18. Ahmed Kheiri & Ender Özcan & Andrew J. Parkes, 2016. "A stochastic local search algorithm with adaptive acceptance for high-school timetabling," Annals of Operations Research, Springer, vol. 239(1), pages 135-151, April.
  19. W. B. Yates & E. C. Keedwell, 2019. "An analysis of heuristic subsequences for offline hyper-heuristic learning," Journal of Heuristics, Springer, vol. 25(3), pages 399-430, June.
  20. Zhang, Yuchang & Bai, Ruibin & Qu, Rong & Tu, Chaofan & Jin, Jiahuan, 2022. "A deep reinforcement learning based hyper-heuristic for combinatorial optimisation with uncertainties," European Journal of Operational Research, Elsevier, vol. 300(2), pages 418-427.
  21. Derya Deliktaş, 2022. "Self-adaptive memetic algorithms for multi-objective single machine learning-effect scheduling problems with release times," Flexible Services and Manufacturing Journal, Springer, vol. 34(3), pages 748-784, September.
  22. Raidl, Günther R., 2015. "Decomposition based hybrid metaheuristics," European Journal of Operational Research, Elsevier, vol. 244(1), pages 66-76.
  23. Sabir, Zulqurnain & Saoud, Sahar & Raja, Muhammad Asif Zahoor & Wahab, Hafiz Abdul & Arbi, Adnène, 2020. "Heuristic computing technique for numerical solutions of nonlinear fourth order Emden–Fowler equation," Mathematics and Computers in Simulation (MATCOM), Elsevier, vol. 178(C), pages 534-548.
  24. Hongbo Li & Guozhong Feng & Minghao Yin, 2020. "On combining variable ordering heuristics for constraint satisfaction problems," Journal of Heuristics, Springer, vol. 26(4), pages 453-474, August.
  25. Drake, John H. & Kheiri, Ahmed & Özcan, Ender & Burke, Edmund K., 2020. "Recent advances in selection hyper-heuristics," European Journal of Operational Research, Elsevier, vol. 285(2), pages 405-428.
  26. Sean P. Walton & M. Rowan Brown, 2019. "Predicting effective control parameters for differential evolution using cluster analysis of objective function features," Journal of Heuristics, Springer, vol. 25(6), pages 1015-1031, December.
  27. Helga Ingimundardottir & Thomas Philip Runarsson, 2018. "Discovering dispatching rules from data using imitation learning: A case study for the job-shop problem," Journal of Scheduling, Springer, vol. 21(4), pages 413-428, August.
  28. Lale Özbakır & Gökhan Seçme, 2022. "A hyper-heuristic approach for stochastic parallel assembly line balancing problems with equipment costs," Operational Research, Springer, vol. 22(1), pages 577-614, March.
  29. Karimi-Mamaghan, Maryam & Mohammadi, Mehrdad & Meyer, Patrick & Karimi-Mamaghan, Amir Mohammad & Talbi, El-Ghazali, 2022. "Machine learning at the service of meta-heuristics for solving combinatorial optimization problems: A state-of-the-art," European Journal of Operational Research, Elsevier, vol. 296(2), pages 393-422.
  30. Johnes, Jill, 2015. "Operational Research in education," European Journal of Operational Research, Elsevier, vol. 243(3), pages 683-696.
  31. Ahmed Kheiri, 2020. "Heuristic Sequence Selection for Inventory Routing Problem," Transportation Science, INFORMS, vol. 54(2), pages 302-312, March.
  32. Nelishia Pillay, 2016. "A review of hyper-heuristics for educational timetabling," Annals of Operations Research, Springer, vol. 239(1), pages 3-38, April.
  33. Swan, Jerry & Adriaensen, Steven & Brownlee, Alexander E.I. & Hammond, Kevin & Johnson, Colin G. & Kheiri, Ahmed & Krawiec, Faustyna & Merelo, J.J. & Minku, Leandro L. & Özcan, Ender & Pappa, Gisele L, 2022. "Metaheuristics “In the Large”," European Journal of Operational Research, Elsevier, vol. 297(2), pages 393-406.
  34. Müller, David & Müller, Marcus G. & Kress, Dominik & Pesch, Erwin, 2022. "An algorithm selection approach for the flexible job shop scheduling problem: Choosing constraint programming solvers through machine learning," European Journal of Operational Research, Elsevier, vol. 302(3), pages 874-891.
  35. Aleksandra Swiercz & Wojciech Frohmberg & Michal Kierzynka & Pawel Wojciechowski & Piotr Zurkowski & Jan Badura & Artur Laskowski & Marta Kasprzak & Jacek Blazewicz, 2018. "GRASShopPER—An algorithm for de novo assembly based on GPU alignments," PLOS ONE, Public Library of Science, vol. 13(8), pages 1-23, August.
  36. Mallol-Poyato, R. & Salcedo-Sanz, S. & Jiménez-Fernández, S. & Díaz-Villar, P., 2015. "Optimal discharge scheduling of energy storage systems in MicroGrids based on hyper-heuristics," Renewable Energy, Elsevier, vol. 83(C), pages 13-24.
  37. Li, Wenwen & Özcan, Ender & John, Robert, 2017. "Multi-objective evolutionary algorithms and hyper-heuristics for wind farm layout optimisation," Renewable Energy, Elsevier, vol. 105(C), pages 473-482.
  38. Mosadegh, H. & Fatemi Ghomi, S.M.T. & Süer, G.A., 2020. "Stochastic mixed-model assembly line sequencing problem: Mathematical modeling and Q-learning based simulated annealing hyper-heuristics," European Journal of Operational Research, Elsevier, vol. 282(2), pages 530-544.
  39. Stefan Vonolfen & Michael Affenzeller, 2016. "Distribution of waiting time for dynamic pickup and delivery problems," Annals of Operations Research, Springer, vol. 236(2), pages 359-382, January.
  40. Jari Kyngäs & Kimmo Nurmi & Nico Kyngäs & George Lilley & Thea Salter & Dries Goossens, 2017. "Scheduling the Australian Football League," Journal of the Operational Research Society, Palgrave Macmillan;The OR Society, vol. 68(8), pages 973-982, August.
  41. Yunna Tian & Dongni Li & Pengyu Zhou & Rongtao Guo & Zhaohe Liu, 2018. "An ACO-based hyperheuristic with dynamic decision blocks for intercell scheduling," Journal of Intelligent Manufacturing, Springer, vol. 29(8), pages 1905-1921, December.
  42. Alberto Santini & Stefan Ropke & Lars Magnus Hvattum, 2018. "A comparison of acceptance criteria for the adaptive large neighbourhood search metaheuristic," Journal of Heuristics, Springer, vol. 24(5), pages 783-815, October.
  43. Kumar, K. Prakash & Saravanan, B., 2017. "Recent techniques to model uncertainties in power generation from renewable energy sources and loads in microgrids – A review," Renewable and Sustainable Energy Reviews, Elsevier, vol. 71(C), pages 348-358.
  44. Nelishia Pillay & Ender Özcan, 2019. "Automated generation of constructive ordering heuristics for educational timetabling," Annals of Operations Research, Springer, vol. 275(1), pages 181-208, April.
  45. Longlong Leng & Yanwei Zhao & Zheng Wang & Jingling Zhang & Wanliang Wang & Chunmiao Zhang, 2019. "A Novel Hyper-Heuristic for the Biobjective Regional Low-Carbon Location-Routing Problem with Multiple Constraints," Sustainability, MDPI, vol. 11(6), pages 1-31, March.
  46. Abbas Tarhini & Kassem Danach & Antoine Harfouche, 2022. "Swarm intelligence-based hyper-heuristic for the vehicle routing problem with prioritized customers," Annals of Operations Research, Springer, vol. 308(1), pages 549-570, January.
  47. Sara Ceschia & Rosita Guido & Andrea Schaerf, 2020. "Solving the static INRC-II nurse rostering problem by simulated annealing based on large neighborhoods," Annals of Operations Research, Springer, vol. 288(1), pages 95-113, May.
  48. Surafel Luleseged Tilahun & Mohamed A. Tawhid, 2019. "Swarm hyperheuristic framework," Journal of Heuristics, Springer, vol. 25(4), pages 809-836, October.
  49. Issam AlHadid & Khalid Kaabneh & Hassan Tarawneh, 2018. "Hybrid Simulated Annealing with Meta-Heuristic Methods to Solve UCT Problem," Modern Applied Science, Canadian Center of Science and Education, vol. 12(11), pages 385-385, November.
  50. Soria-Alcaraz, Jorge A. & Ochoa, Gabriela & Swan, Jerry & Carpio, Martin & Puga, Hector & Burke, Edmund K., 2014. "Effective learning hyper-heuristics for the course timetabling problem," European Journal of Operational Research, Elsevier, vol. 238(1), pages 77-86.
  51. Stefan Vonolfen & Michael Affenzeller, 2016. "Distribution of waiting time for dynamic pickup and delivery problems," Annals of Operations Research, Springer, vol. 236(2), pages 359-382, January.
  52. Olacir R. Castro & Gian Mauricio Fritsche & Aurora Pozo, 2018. "Evaluating selection methods on hyper-heuristic multi-objective particle swarm optimization," Journal of Heuristics, Springer, vol. 24(4), pages 581-616, August.
  53. Aleksandra Swiercz & Edmund Burke & Mateusz Cichenski & Grzegorz Pawlak & Sanja Petrovic & Tomasz Zurkowski & Jacek Blazewicz, 2014. "Unified encoding for hyper-heuristics with application to bioinformatics," Central European Journal of Operations Research, Springer;Slovak Society for Operations Research;Hungarian Operational Research Society;Czech Society for Operations Research;Österr. Gesellschaft für Operations Research (ÖGOR);Slovenian Society Informatika - Section for Operational Research;Croatian Operational Research Society, vol. 22(3), pages 567-589, September.
  54. Kheiri, Ahmed & Özcan, Ender, 2016. "An iterated multi-stage selection hyper-heuristic," European Journal of Operational Research, Elsevier, vol. 250(1), pages 77-90.
  55. Venkatesh Pandiri & Alok Singh, 2021. "A simple hyper-heuristic approach for a variant of many-to-many hub location-routing problem," Journal of Heuristics, Springer, vol. 27(5), pages 791-868, October.
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