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Early years of Biased Random-Key Genetic Algorithms: A systematic review (2405.01765v3)

Published 2 May 2024 in cs.NE and math.OC

Abstract: This paper presents a systematic literature review and bibliometric analysis focusing on Biased Random-Key Genetic Algorithms (BRKGA). BRKGA is a metaheuristic framework that uses random-key-based chromosomes with biased, uniform, and elitist mating strategies alongside a genetic algorithm. This review encompasses around~250 papers, covering a diverse array of applications ranging from classical combinatorial optimization problems to real-world industrial scenarios, and even non-traditional applications like hyperparameter tuning in machine learning and scenario generation for two-stage problems. In summary, this study offers a comprehensive examination of the BRKGA metaheuristic and its various applications, shedding light on key areas for future research.

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References (85)
  1. Evolutionary algorithm for the k𝑘kitalic_k-interconnected multi-depot multi-traveling salesmen problem. In Proceedings of the 15th Annual Conference on Genetic and Evolutionary Computation, GECCO’13, pages 463–470, New York, NY, USA, 2013. ACM. ISBN 978-1-4503-1963-8. doi: 10.1145/2463372.2463434.
  2. Biased random-key genetic algorithms for the winner determination problem in combinatorial auctions. Evolutionary Computation, 23(2):279–307, 2015. ISSN 10636560 (ISSN). doi: 10.1162/EVCO\_a\_00138.
  3. Scheduling software updates for connected cars with limited availability. Applied Soft Computing Journal, 82:105575, 2019a. ISSN 15684946 (ISSN). doi: 10.1016/j.asoc.2019.105575.
  4. Minimizing flowtime in a flowshop scheduling problem with a biased random-key genetic algorithm. Expert Systems with Applications, 128:67–80, 2019b. ISSN 09574174 (ISSN). doi: 10.1016/j.eswa.2019.03.007.
  5. The multi-parent biased random-key genetic algorithm with implicit path-relinking and its real-world applications. European Journal of Operational Research, 289(1):17–30, 2021. ISSN 03772217 (ISSN). doi: 10.1016/j.ejor.2019.11.037.
  6. Evolutionary algorithms for overlapping correlation clustering. In Proceedings of the 16th Conference on Genetic and Evolutionary Computation, GECCO’14, pages 405–412, New York, NY, USA, 2014. ACM. ISBN 978-1-4503-2662-9. doi: 10.1145/2576768.2598284.
  7. The physical cell identity assignment problem: a practical optimization approach. IEEE Transactions on Evolutionary Computation, pages 1–1, 2022. ISSN 1089-778X. doi: 10.1109/TEVC.2022.3185927. To appear.
  8. Balancing parallel assembly lines with disabled workers. European Journal of Industrial Engineering, 9(3):344–365, 2015. ISSN 17515254 (ISSN). doi: 10.1504/EJIE.2015.069343.
  9. M. Aria and C. Cuccurullo. bibliometrix: An r-tool for comprehensive science mapping analysis. Journal of informetrics, 11(4):959–975, 2017. doi: 10.1016/j.joi.2017.08.007.
  10. Scopus as a curated, high-quality bibliometric data source for academic research in quantitative science studies. Quantitative Science Studies, 1(1):377–386, 2020. doi: 10.1162/qss_a_00019.
  11. J. C. Bean. Genetic algorithms and random keys for sequencing and optimization. ORSA Journal on Computing, 6(2):154–160, 1994. doi: 10.1287/ijoc.6.2.154.
  12. Nuno C. L. F. Beirão. Sistema de apoio à decisão para sequenciamento de operaçÔes em ambientes Job Shop. PhD thesis, University of Porto, 1997. URL https://repositorio-aberto.up.pt/handle/10216/12242.
  13. F-race and iterated f-race: An overview. Experimental methods for the analysis of optimization algorithms, pages 311–336, 2010. doi: 10.1007/978-3-642-02538-9\_13.
  14. Co-citation analysis, bibliographic coupling, and direct citation: Which citation approach represents the research front most accurately? Journal of the American Society for information Science and Technology, 61(12):2389–2404, 2010. doi: 10.1002/asi.21419.
  15. A biased random-key genetic algorithm for single-round divisible load scheduling. International Transactions in Operational Research, 22(5):823–839, 2015. ISSN 09696016 (ISSN). doi: 10.1111/itor.12178.
  16. A hybrid genetic algorithm for the weight setting problem in ospf/is-is routing. Networks, 46(1):36–56, 2005. doi: 10.1002/net.20070.
  17. A biased random-key genetic algorithm for road congestion minimization. Optimization Letters, 4(4):619–633, 2010. ISSN 18624472 (ISSN). doi: 10.1007/s11590-010-0226-6.
  18. Co-word analysis as a tool for describing the network of interactions between basic and technological research: The case of polymer chemsitry. Scientometrics, 22(1):155–205, 1991. doi: 10.1007/BF02019280.
  19. M. Caserta and T. Reiners. A pool-based pattern generation algorithm for logical analysis of data with automatic fine-tuning. European Journal of Operational Research, 248(2):593–606, 2016. ISSN 03772217 (ISSN). doi: 10.1016/j.ejor.2015.05.078.
  20. Science mapping software tools: Review, analysis, and cooperative study among tools. Journal of the American Society for information Science and Technology, 62(7):1382–1402, 2011. doi: 10.1002/asi.21525.
  21. Harris Cooper. Research synthesis and meta-analysis: A step-by-step approach, volume 2. Sage publications, 2015.
  22. A fast and elitist multiobjective genetic algorithm: Nsga-ii. IEEE transactions on evolutionary computation, 6(2):182–197, 2002. doi: 10.1109/4235.996017.
  23. Improved heuristics for the regenerator location problem. International Transactions in Operational Research, 21(4):541–558, 2014. ISSN 09696016 (ISSN). doi: 10.1111/itor.12085.
  24. Elsevier. Scopus. https://www.scopus.com, 2024. Accessed on 2024-03-24.
  25. A genetic algorithm for the weight setting problem in OSPF routing. Journal of Combinatorial Optimization, 6(3):299–333, 2002. ISSN 1382-6905. doi: 10.1023/A:1014852026591.
  26. Microaggregation heuristic applied to statistical disclosure control. Information Sciences, 548:37–55, 2021. ISSN 00200255 (ISSN). doi: 10.1016/j.ins.2020.09.069.
  27. Thomas A Feo and Mauricio G. C. Resende. Greedy randomized adaptive search procedures. Journal of global optimization, 6(2):109–133, 1995. doi: 10.1007/BF01096763.
  28. P. Festa. A biased random-key genetic algorithm for data clustering. Mathematical Biosciences, 245(1):76–85, 2013. ISSN 00255564 (ISSN). doi: 10.1016/j.mbs.2013.07.011.
  29. Automatic tuning of grasp with path-relinking heuristics with a biased random-key genetic algorithm. Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), 6049 LNCS:338–349, 2010. doi: 10.1007/978-3-642-13193-6_29.
  30. Computers and intractability, volume 174. freeman San Francisco, 1979.
  31. Understanding the role of logistics capabilities in achieving supply chain agility: a systematic literature review. Supply Chain Management: An International Journal, 2012. doi: 10.1108/13598541211246594.
  32. David E. Goldberg. Genetic Algorithms in Search, Optimization and Machine Learning. Addison-Wesley Publishing Company, 1989.
  33. J. F. Gonçalves. A hybrid genetic algorithm-heuristic for a two-dimensional orthogonal packing problem. European Journal of Operational Research, 183(3):1212–1229, 2007. ISSN 03772217 (ISSN). doi: 10.1016/j.ejor.2005.11.062.
  34. A hybrid genetic algorithm for assembly line balancing. Journal of Heuristics, 8(6):629–642, 2002. ISSN 13811231 (ISSN). doi: 10.1023/A:1020377910258.
  35. An evolutionary algorithm for manufacturing cell formation. Computers and Industrial Engineering, 47(2-3):247–273, 2004. ISSN 03608352 (ISSN). doi: 10.1016/j.cie.2004.07.003.
  36. Biased random-key genetic algorithms for combinatorial optimization. Journal of Heuristics, 17(5):487–525, 2011a. ISSN 13811231 (ISSN). doi: 10.1007/s10732-010-9143-1.
  37. A parallel multi-population genetic algorithm for a constrained two-dimensional orthogonal packing problem. Journal of Combinatorial Optimization, 22(2):180–201, 2011b. ISSN 13826905 (ISSN). doi: 10.1007/s10878-009-9282-1.
  38. A parallel multi-population biased random-key genetic algorithm for a container loading problem. Computers and Operations Research, 39(2):179–190, 2012. ISSN 03050548 (ISSN). doi: 10.1016/j.cor.2011.03.009.
  39. A biased random key genetic algorithm for 2d and 3d bin packing problems. International Journal of Production Economics, 145(2):500–510, 2013. ISSN 09255273 (ISSN). doi: 10.1016/j.ijpe.2013.04.019.
  40. A biased random-key genetic algorithm for the unequal area facility layout problem. European Journal of Operational Research, 246(1):86–107, 2015. ISSN 03772217 (ISSN). doi: 10.1016/j.ejor.2015.04.029.
  41. A genetic algorithm for lot sizing and scheduling under capacity constraints and allowing backorders. International Journal of Production Research, 49(9):2683–2703, 2011. ISSN 00207543 (ISSN). doi: 10.1080/00207543.2010.532936.
  42. J. F. Gonçalves and G. WĂ€scher. A mip model and a biased random-key genetic algorithm based approach for a two-dimensional cutting problem with defects. European Journal of Operational Research, 286(3):867–882, 2020. ISSN 03772217 (ISSN). doi: 10.1016/j.ejor.2020.04.028.
  43. José F. Gonçalves and Nuno C. L. F. BeirĂŁo. Um algoritmo genĂ©tico baseado em chave aleatĂłrias para sequenciamento de opearçÔes. Investigação Operacional, 19:123–137, 1999.
  44. A cloud brokerage approach for solving the resource management problem in multi-cloud environments. Computers and Industrial Engineering, 95:16–26, 2016. ISSN 03608352 (ISSN). doi: 10.1016/j.cie.2016.02.015.
  45. Kernel methods in machine learning. The Annals of Statistics, 36(3):1171–1220, 2008. doi: 10.1214/009053607000000677.
  46. John H Holland. Adaptation in natural and artificial systems: An introductory analysis with applications to biology, control, and artificial intelligence. U Michigan Press, 1975.
  47. Methods for solving road network problems with disruptions. Electronic Notes in Discrete Mathematics, 64:175–184, 2018. ISSN 15710653 (ISSN). doi: 10.1016/j.endm.2018.01.019.
  48. Near-optimal disjoint-path facility location through set cover by pairs. Operations Research, 68(3):896–926, 2020. doi: 10.1287/opre.2019.1956.
  49. A matheuristic approach for the minimum broadcast time problem using a biased random-key genetic algorithm. International Transactions in Operational Research, pages 246–273, 2022. doi: 10.1111/itor.13146.
  50. Exact and heuristic approaches for the root sequence index allocation problem. Applied Soft Computing, 130:109634, 2022. doi: 10.1016/j.asoc.2022.109634.
  51. Biased random-key genetic algorithms: A review. European Journal of Operational Research, 2024. doi: 10.1016/j.ejor.2024.03.030.
  52. Heuristics for a hub location-routing problem. Networks, 68(1):54–90, 2016. ISSN 00283045 (ISSN). doi: 10.1002/net.21685.
  53. The irace package: Iterated racing for automatic algorithm configuration. Operations Research Perspectives, 3:43–58, 2016. doi: 10.1016/j.orp.2016.09.002.
  54. Unrelated parallel machine scheduling with eligibility constraints and delivery times to minimize total weighted tardiness. Computers & Operations Research, 149:105999, 2023. doi: 10.1016/j.cor.2022.105999.
  55. Mersenne twister: a 623-dimensionally equidistributed uniform pseudo-random number generator. ACM Transactions on Modeling and Computer Simulation (TOMACS), 8(1):3–30, 1998. doi: 10.1145/272991.272995.
  56. Hybrid metaheuristics to solve a multiproduct two-stage capacitated facility location problem. International Transactions in Operational Research, 28(6):3069–3093, 2021. ISSN 09696016 (ISSN). doi: 10.1111/itor.12930.
  57. A random key based genetic algorithm for the resource constrained project scheduling problem. Computers and Operations Research, 36(1):92–109, 2009. ISSN 03050548 (ISSN). doi: 10.1016/j.cor.2007.07.001.
  58. A bibliometric analysis of operations research and management science. Omega, 73:37–48, 2017. doi: 10.1016/j.omega.2016.12.004.
  59. Variable neighborhood search. Computers & operations research, 24(11):1097–1100, 1997. doi: 10.1016/S0305-0548(97)00031-2.
  60. L. Mönch and S. Roob. A matheuristic framework for batch machine scheduling problems with incompatible job families and regular sum objective. Applied Soft Computing Journal, 68:835–846, 2018. ISSN 15684946 (ISSN). doi: 10.1016/j.asoc.2017.10.028.
  61. Simple heuristics for the assembly line worker assignment and balancing problem. Journal of Heuristics, 18(3):505–524, 2012. ISSN 13811231 (ISSN). doi: 10.1007/s10732-012-9195-5.
  62. A biased random-key genetic algorithm for routing and wavelength assignment. Journal of Global Optimization, 50(3):503–518, 2011. ISSN 09255001 (ISSN). doi: 10.1007/s10898-010-9608-7.
  63. Reinforced genetic algorithm learning for optimizing computation graphs. In Proceedings of the 8th International Conference on Learning Representations, ICLR’ 20, pages 1–13, 2020. URL https://openreview.net/pdf?id=rkxDoJBYPB.
  64. How to use bibexcel for various types of bibliometric analysis. Celebrating scholarly communication studies: A Festschrift for Olle Persson at his 60th Birthday, 5:9–24, 2009.
  65. A new load balance methodology for container loading problem in road transportation. European Journal of Operational Research, 266(3):1140–1152, 2018. ISSN 03772217 (ISSN). doi: 10.1016/j.ejor.2017.10.050.
  66. Robust meter placement for state estimation considering distribution network reconfiguration for annual energy loss reduction. Electric Power Systems Research, 182:106233, 2020. ISSN 03787796 (ISSN). doi: 10.1016/j.epsr.2020.106233.
  67. A biased random-key genetic algorithm for ospf and deft routing to minimize network congestion. International Transactions in Operational Research, 18(3):401–423, 2011. ISSN 09696016 (ISSN). doi: 10.1111/j.1475-3995.2010.00771.x.
  68. Mauricio G. C. Resende. Biased random-key genetic algorithms with applications in telecommunications. Top, 20(1):130–153, 2012. doi: 10.1007/s11750-011-0176-x.
  69. J. Rocholl and L. Mönch. Decomposition heuristics for parallel-machine multiple orders per job scheduling problems with a common due date. Journal of the Operational Research Society, 72(8):1737–1753, 2021. ISSN 01605682 (ISSN). doi: 10.1080/01605682.2019.1640589.
  70. A biased random-key genetic algorithm for the capacitated minimum spanning tree problem. Computers and Operations Research, 57:95–108, 2015. ISSN 03050548 (ISSN). doi: 10.1016/j.cor.2014.11.011.
  71. Survivable ip/mpls-over-wson multilayer network optimization. Journal of Optical Communications and Networking, 3(8):629–640, 2011. ISSN 19430620 (ISSN). doi: 10.1364/JOCN.3.000629.
  72. The dial-a-ride problem with private fleet and common carrier. Computers & Operations Research, 147:105933, 2022. doi: 10.1016/j.cor.2022.105933.
  73. Conducting content-analysis based literature reviews in supply chain management. Supply Chain Management: An International Journal, 2012. doi: 10.1108/13598541211258609.
  74. A python/c++ library for bound-constrained global optimization using a biased random-key genetic algorithm. Journal of Combinatorial Optimization, 30(3):710–728, 2015. ISSN 13826905 (ISSN). doi: 10.1007/s10878-013-9659-z.
  75. The multicommodity traveling salesman problem with priority prizes: a mathematical model and metaheuristics. Computational and Applied Mathematics, 38(4):188, 2019. ISSN 22383603 (ISSN). doi: 10.1007/s40314-019-0976-4.
  76. The journal coverage of web of science, scopus and dimensions: A comparative analysis. Scientometrics, 126(6):5113–5142, 2021. doi: 10.1007/s11192-021-03948-5.
  77. A random-key genetic algorithm for the generalized traveling salesman problem. European Journal of Operational Research, 174(1):38–53, 2006. ISSN 03772217 (ISSN). doi: 10.1016/j.ejor.2004.09.057.
  78. An analysis of multi-point crossover. In Foundations of genetic algorithms, volume 1, pages 301–315. Elsevier, 1991. doi: 10.1016/B978-0-08-050684-5.50022-7.
  79. A multi-objective local search heuristic for scheduling earth observations taken by an agile satellite. European Journal of Operational Research, 245(2):542–554, 2015. ISSN 03772217 (ISSN). doi: 10.1016/j.ejor.2015.03.011.
  80. Similarities and contrasts of complexity, uncertainty, risks, and resilience in supply chains and temporary multi-organization projects. International Journal of Project Management, 34(7):1328–1346, 2016a. doi: 10.1016/j.ijproman.2015.10.012.
  81. Conducting systematic literature review in operations management. Production Planning & Control, 27(5):408–420, 2016b. doi: 10.1080/09537287.2015.1129464.
  82. A c++ application programming interface for biased random-key genetic algorithms. Optimization Methods and Software, 30(1):81–93, 2015. ISSN 10556788 (ISSN). doi: 10.1080/10556788.2014.890197.
  83. Accessible location of mobile labs for covid-19 testing. Health Care Management Science, pages 1–19, 2022. doi: 10.1007/s10729-022-09614-3.
  84. Analyzing the past to prepare for the future: Writing a literature review. MIS quarterly, pages xiii–xxiii, 2002.
  85. Supply chain scheduling method for the coordination of agile production and port delivery operation. Mathematics, 11(15):3276, 2023. doi: 10.3390/math11153276.

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