List of genetic algorithm applications

This is a list of genetic algorithm (GA) applications.

Natural Sciences, Mathematics and Computer Science

• Bayesian inference links to particle methods in Bayesian statistics and hidden Markov chain models ^{[1] [2]}
• Artificial creativity
• Chemical kinetics (gas and solid phases)
• Calculation of bound states and local-density approximations
• Code-breaking, using the GA to search large solution spaces of ciphers for the one correct decryption. ^[3]
• Computer architecture: using GA to find out weak links in approximate computing such as lookahead.
• Configuration applications, particularly physics applications of optimal molecule configurations for particular systems like C₆₀ (buckyballs)
• Construction of facial composites of suspects by eyewitnesses in forensic science. ^[4]
• Data Center/Server Farm. ^[5]
• Distributed computer network topologies
• Electronic circuit design, known as evolvable hardware
• Evolutionary image processing
• Feature selection for Machine Learning ^[6]
• Feynman-Kac models ^{[7] [8] [9]}
• File allocation for a distributed system
• Filtering and signal processing ^{[10] [11]}
• Finding hardware bugs. ^{[12] [13]}
• Game theory equilibrium resolution
• Genetic Algorithm for Rule Set Production
• Scheduling applications, including job-shop scheduling and scheduling in printed circuit board assembly. ^[14] The objective being to schedule jobs in a sequence-dependent or non-sequence-dependent setup environment in order to maximize the volume of production while minimizing penalties such as tardiness. Satellite communication scheduling for the NASA Deep Space Network was shown to benefit from genetic algorithms. ^[15]
• Learning robot behavior using genetic algorithms
• Image processing: Dense pixel matching ^[16]
• Learning fuzzy rule base using genetic algorithms
• Molecular structure optimization (chemistry)
• Optimisation of data compression systems, for example using wavelets.
• Power electronics design. ^[17]
• Traveling salesman problem and its applications ^[14]
• Stopping propagations, i.e. deciding how to cut edges in a graph so that some infectious condition (e.g. a disease, fire, computer virus, etc.) stops its spread. A bi-level genetic algorithm (i.e. a genetic algorithm where the fitness of each individual is calculated by running another genetic algorithm) was used due to the Σ^P₂-completeness of the problem. ^[18]

Earth Sciences

• Climatology: Estimation of heat flux between the atmosphere and sea ice ^[19]
• Climatology: Modelling global temperature changes ^[20]
• Design of water resource systems ^[21]
• Groundwater monitoring networks ^[22]

Finance and Economics

• Financial mathematics ^{[2] [23]}
  • Real options valuation ^[24]
  • Portfolio optimization ^[25]
• Genetic algorithm in economics
  • Representing rational agents in economic models such as the cobweb model
  • the same, in Agent-based computational economics generally, and in artificial financial markets

Social Sciences

• Design of anti-terrorism systems ^[26]
• Linguistic analysis, including grammar induction and other aspects of Natural language processing (NLP) such as word-sense disambiguation.
• Finding the optimum subset of questions from a candidate pool of questions in psychological test design ^[27]

Industry, Management and Engineering

• Audio watermark insertion/detection
• Airlines revenue management ^[28]
• Automated design of mechatronic systems using bond graphs and genetic programming (NSF)
• Automated design of industrial equipment using catalogs of exemplar lever patterns
• Automated design, including research on composite material design and multi-objective design of automotive components for crashworthiness, weight savings, and other characteristics
• Automated planning of structural inspection ^[29]
• Container loading optimization
• Control engineering, ^{[30] [31] [32] [33]}
• Marketing mix analysis
• Mechanical engineering ^{[34] [35]}
• Mobile communications infrastructure optimization.
• Plant floor layout
• Pop music record production ^[36]
• Quality control
• Sorting network
• Timetabling problems, such as designing a non-conflicting class timetable for a large university
• Vehicle routing problem ^[37]
• Optimal bearing placement ^[38]
• Computer-automated design ^[39]

Biological Sciences and Bioinformatics

• Bioinformatics Multiple Sequence Alignment ^{[40] [41] [42]}
• Bioinformatics: RNA structure prediction ^[43]
• Bioinformatics: Motif Discovery ^[44]
• Biology and computational chemistry ^{[45] [46]}
• Building phylogenetic trees. ^[47]
• Gene expression profiling analysis. ^[48]
• Medicine: Clinical decision support in ophthalmology ^[49] and oncology ^[50]
• Computational Neuroscience: finding values for the maximal conductances of ion channels in biophysically detailed neuron models ^[51]
• Protein folding and protein/ligand docking ^{[52] [53]}
• Selection of optimal mathematical model to describe biological systems
• Operon prediction. ^[54]

General Applications

• Neural Networks; particularly recurrent neural networks ^[55]
• Training artificial neural networks when pre-classified training examples are not readily obtainable (neuroevolution)

Physics

• Optimization of beam dynamics in accelerator physics. ^[56]
• Design of particle accelerator beamlines ^[57]

Other Applications

• Clustering, using genetic algorithms to optimize a wide range of different fit-functions.^{[ dead link ] [58]}
• Multidimensional systems
• Multimodal Optimization ^{[59] [60] [61]}
• Multiple criteria production scheduling ^[62]
• Multiple population topologies and interchange methodologies
• Mutation testing
• Parallelization of GAs/GPs including use of hierarchical decomposition of problem domains and design spaces nesting of irregular shapes using feature matching and GAs.
• Rare event analysis ^{[63] [64]}
• Solving the machine-component grouping problem required for cellular manufacturing systems
• Stochastic optimization ^[65]
• Tactical asset allocation and international equity strategies
• Wireless sensor/ad-hoc networks. ^[66]

References

1. "Del Moral - Bayesian Statistics". u-bordeaux1.fr. Archived from the original on 2012-05-01. Retrieved 2011-12-29.
2. a tutorial on genetic particle models
3. Joachim De Zutter
4. Craig Aaen Stockdale (June 1, 2008). "A (r)evolution in Crime-fighting". Forensic Magazine.
5. SymbioticSphere – Distributed Software Systems Group, University of Massachusetts, Boston Archived 2009-03-29 at the Wayback Machine
6. "Evolutionary Algorithms for Feature Selection". www.kdnuggets.com. Retrieved 2018-02-19.
7. "Website for Feynman-Kac particle models". u-bordeaux1.fr. Archived from the original on 2012-05-01.
8. "a review article on genetic particle models". Archived from the original on 2012-05-01. Retrieved 2011-12-29.
9. "Feynman-Kac Formulae". u-bordeaux1.fr. Archived from the original on 2012-05-01. Retrieved 2011-12-29.
10. "links to particle filters". Archived from the original on 2012-05-01. Retrieved 2011-12-29.
11. a tutorial on genetic particle models
12. Hitoshi Iba, Sumitaka Akiba, Tetsuya Higuchi, Taisuke Sato: BUGS: A Bug-Based Search Strategy using Genetic Algorithms. PPSN 1992:
13. Ibrahim, W. and Amer, H.: An Adaptive Genetic Algorithm for VLSI Test Vector Selection
14. Maimon, Oded; Braha, Dan (1998). "A genetic algorithm approach to scheduling PCBs on a single machine" (PDF). International Journal of Production Research. 36 (3): 3. CiteSeerX   10.1.1.129.9504 . doi:10.1080/002075498193688.
15. Guillaume, Alexandre; Lee, Seugnwon; Wang, Yeou-Fang; Zheng, Hua; Hovden, Robert; Chau, Savio; Tung, Yu-Wen; Terrile, Richard J. (2007). "Deep Space Network Scheduling Using Evolutionary Computational Methods". 2007 IEEE Aerospace Conference. pp. 1–6. doi:10.1109/AERO.2007.352900. ISBN   978-1-4244-0524-4. S2CID   15862933.
16. A. dos Santos-Paulino, J.-C. Nebel and F.Florez-Revuelta (2014) Evolutionary algorithm for dense pixel matching in presence of distortions, EvoStar Conference, Granada, Spain, 23–25 April 2014
17. Jun Zhang; Chung, H.S.H.; Lo, W.L. (2006). "Pseudocoevolutionary genetic algorithms for power electronic circuits optimization" (PDF). IEEE Transactions on Systems, Man, and Cybernetics - Part C: Applications and Reviews. 36 (4): 590–598. Bibcode:2006ITHMS..36..590Z. doi:10.1109/TSMCC.2005.855497. Archived from the original (PDF) on 2011-07-07. Retrieved 2010-08-09.
18. Galiana, J.; Rodríguez, I.; Rubio, F. (2023). "How to stop undesired propagations by using bi-level genetic algorithms". Applied Soft Computing. 136 (110094) 110094. doi: 10.1016/j.asoc.2023.110094 .
19. Karolina Stanislawska; Krzysztof Krawiec; Timo Vihma (July 15, 2015). "Genetic Programming for Estimation of Heat Flux between the Atmosphere and Sea Ice in Polar Regions". Proceedings of the 2015 Annual Conference on Genetic and Evolutionary Computation. pp. 1279–1286. doi:10.1145/2739480.2754675. ISBN   978-1-4503-3472-3. S2CID   2879084.
20. Karolina Stanislawska; Krzysztof Krawiec; Zbigniew W. Kundzewicz (April 2012). "Modelling global temperature changes with genetic programming". Computers and Mathematics with Applications. 64 (12): 3717–3728. doi: 10.1016/j.camwa.2012.02.049 .
21. Zhang, S.X.; Babovic, V. (2012). "A real options approach to the design and architecture of water supply systems using innovative water technologies under uncertainty". Journal of Hydroinformatics. 14 (1): 13–29. doi: 10.2166/hydro.2011.078 .
22. Optimization of Water-level Monitoring Networks in the Eastern Snake River Plain Aquifer Using a Kriging-based Genetic Algorithm Method United States Geological Survey
23. "Del Moral - Financial Mathematics". u-bordeaux1.fr. Archived from the original on 2012-12-11. Retrieved 2011-12-29.
24. Zhang, S.X.; Babovic, V. (2011). "An evolutionary real options framework for the design and management of projects and systems with complex real options and exercising conditions". Decision Support Systems. 51 (1): 119–129. doi:10.1016/j.dss.2010.12.001. S2CID   15362734.
25. Sefiane, Slimane and Benbouziane, Mohamed (2012). Portfolio Selection Using Genetic Algorithm Archived 2016-04-29 at the Wayback Machine , Journal of Applied Finance & Banking, Vol. 2, No. 4 (2012): pp. 143-154.
26. Buurman, J.; Zhang, S.X.; Babovic, V. (2009). "Reducing risk through real options in systems design: the case of architecting a maritime domain protection system". Risk Analysis. 29 (3): 366–379. Bibcode:2009RiskA..29..366B. doi:10.1111/j.1539-6924.2008.01160.x. PMID   19076327. S2CID   36370133.
27. van der Linde, I.; Bright, P. (2018). "A genetic algorithm to find optimal reading test word subsets for estimating full-scale IQ". PLOS ONE. 13 (10) e0205754. Bibcode:2018PLoSO..1305754V. doi: 10.1371/journal.pone.0205754 . PMC   6193671 .
28. Aloysius George, B. R. Rajakumar, D. Binu, (2012) "Genetic algorithm based airlines booking terminal open/close decision system"
29. Ellefsen, K.O.; Lepikson, H.A.; Albiez, J.C. (2017). "Multiobjective coverage path planning: Enabling automated inspection of complex, real-world structures". Applied Soft Computing. 61: 264–282. arXiv: 1901.07272 . doi:10.1016/j.asoc.2017.07.051. hdl:10852/58883. ISSN   1568-4946. S2CID   6183350.
30. "CiteSeerX — Citation Query Switching Control Systems and Their Design Automation via Genetic Algorithms". Psu.edu.
31. Li, Y.; et al. (1996). "Genetic algorithm automated approach to design of sliding mode control systems". Int J Control. 63 (4): 721–739. CiteSeerX   10.1.1.43.1654 . doi:10.1080/00207179608921865.
32. Loughborough University Institutional Repository. handle.net (thesis). Loughborough University. 2010-01-18. hdl:2134/5806.
33. Patrascu, M. (2015). "Genetically enhanced modal controller design for seismic vibration in nonlinear multi-damper configuration". Proceedings of the Institution of Mechanical Engineers, Part I. 229 (2): 158–168. doi:10.1177/0959651814550540. S2CID   26599174.
34. "Genetic Algorithms for Engineering Optimization" (PDF).
35. "Applications of evolutionary algorithms in mechanical engineering".
36. "To the beat of the byte". BBC News. 1998-07-01. Retrieved 2010-05-03.
37. Vidal T, Crainic TG, Gendreau M, Lahrichi N, Rei W (2012). "A hybrid genetic algorithm for multidepot and periodic vehicle routing problems" (PDF). Operations Research. 60 (3): 611–624. doi:10.1287/opre.1120.1048.
38. Liu, Shibing; Yang, Bingen (2017). "Optimal placement of water-lubricated rubber bearings for vibration reduction of flexible multistage rotor systems". Journal of Sound and Vibration. 407: 332–349. Bibcode:2017JSV...407..332L. doi:10.1016/j.jsv.2017.07.004.
39. Li, Y.; et al. (2004). "CAutoCSD – Evolutionary search and optimisation enabled computer automated control system design". International Journal of Automation and Computing. 1 (1): 76–88. doi:10.1007/s11633-004-0076-8. S2CID   55417415.
40. Gondro C, Kinghorn BP (2007). "A simple genetic algorithm for multiple sequence alignment". Genetics and Molecular Research. 6 (4): 964–982. PMID   18058716.
41. Notredame C, Higgins DG (1995). "SAGA a Genetic Algorithm for Multiple Sequence Alignment". Nucleic Acids Research. 24 (8): 1515–24. doi:10.1093/nar/24.8.1515. PMC   145823 . PMID   8628686.
42. "Notredame Lab Home Page - Comparative Bioinformatics". tcoffee.org.
43. van Batenburg FH, Gultyaev AP, Pleij CW (1995). "An APL-programmed genetic algorithm for the prediction of RNA secondary structure". Journal of Theoretical Biology. 174 (3): 269–280. Bibcode:1995JThBi.174..269V. doi:10.1006/jtbi.1995.0098. PMID   7545258.
44. Wong, Ka-Chun; Peng, Chengbin; Wong, Man-Hon; Leung, Kwong-Sak (2011). "Generalizing and learning protein-DNA binding sequence representations by an evolutionary algorithm". Soft Computing. 15 (8): 1631–1642. doi:10.1007/s00500-011-0692-5. S2CID   18253131.
45. "Del Moral - Biology & Chemistry". u-bordeaux1.fr. Archived from the original on 2012-05-01. Retrieved 2011-12-29.
46. "an article on genetic particle models". Archived from the original on 2012-05-01. Retrieved 2011-12-29.
47. Hill T, Lundgren A, Fredriksson R, Schiöth HB (2005). "Genetic algorithm for large-scale maximum parsimony phylogenetic analysis of proteins". Biochimica et Biophysica Acta (BBA) - General Subjects. 1725 (1): 19–29. doi:10.1016/j.bbagen.2005.04.027. PMID   15990235.
48. To CC, Vohradsky J (2007). "A parallel genetic algorithm for single class pattern classification and its application for gene expression profiling in Streptomyces coelicolor". BMC Genomics. 8 49. doi: 10.1186/1471-2164-8-49 . PMC   1804277 . PMID   17298664.
49. Krzysztof Krawiec; Mikołaj Pawlak (April 10, 2015). "Genetic Programming with Alternative Search Drivers for Detection of Retinal Blood Vessels".{{cite journal}}: Cite journal requires |journal= (help)
50. Fitzgerald, Jeannie, Ryan, Conor, Medernach, David and Krawiec, Krzysztof (July 15, 2015). "An Integrated Approach to Stage 1 Breast Cancer Detection". Proceedings of the 2015 Annual Conference on Genetic and Evolutionary Computation. pp. 1199–1206. doi:10.1145/2739480.2754761. ISBN   978-1-4503-3472-3. S2CID   14110665.
51. Van Geit, Werner; Gevaert, Michael; Chindemi, Giuseppe; Rössert, Christian; Courcol, Jean-Denis; Muller, Eilif B.; Schürmann, Felix; Segev, Idan; Markram, Henry (7 June 2016). "BluePyOpt: Leveraging Open Source Software and Cloud Infrastructure to Optimise Model Parameters in Neuroscience". Frontiers in Neuroinformatics. 10: 17. arXiv: 1603.00500 . Bibcode:2016arXiv160300500V. doi: 10.3389/fninf.2016.00017 . PMC   4896051 . PMID   27375471.
52. Willett P (1995). "Genetic algorithms in molecular recognition and design". Trends in Biotechnology. 13 (12): 516–521. doi:10.1016/S0167-7799(00)89015-0. PMID   8595137.
53. Wong, Ka-Chun; Leung, Kwong-Sak; Wong, Man-Hon (2010). "Protein structure prediction on a lattice model via multimodal optimization techniques". Proceedings of the 12th annual conference on Genetic and evolutionary computation. p. 155. doi:10.1145/1830483.1830513. ISBN   978-1-4503-0072-8. S2CID   14651808.{{cite book}}: |work= ignored (help)
54. Wang S, Wang Y, Du W, Sun F, Wang X, Zhou C, Liang Y (2007). "A multi-approaches-guided genetic algorithm with application to operon prediction". Artificial Intelligence in Medicine. 41 (2): 151–159. doi:10.1016/j.artmed.2007.07.010. PMID   17869072.
55. "Applying Genetic Algorithms to Recurrent Neural Networks for Learning Network Parameters and Architecture". arimaa.com.
56. Bacci, A.; Petrillo, V.; Rossetti Conti, M. (2016). "GIOTTO: A Genetic Code for Demanding Beam-dynamics Optimizations" (PDF). International Particle Accelerator Conference (7th). Joint Accelerator Conferences Website (JACoW). doi:10.18429/JACoW-IPAC2016-WEPOY039. WEPOY039.
57. Rossetti Conti, M.; Bacci, A. (2018). "Electron beam transfer line design for plasma driven Free Electron Lasers". Nuclear Instruments and Methods in Physics Research Section A: Accelerators, Spectrometers, Detectors and Associated Equipment. 909: 84–89. arXiv: 1803.00431 . Bibcode:2018NIMPA.909...84R. doi:10.1016/j.nima.2018.02.061. ISSN   0168-9002. S2CID   56365602.
58. Auffarth, B. (2010). Clustering by a Genetic Algorithm with Biased Mutation Operator. WCCI CEC. IEEE, July 18–23, 2010. http://citeseerx.ist.psu.edu/viewdoc/summary?doi=10.1.1.170.869%5B%5D
59. Wong, Ka-Chun; Leung, Kwong-Sak; Wong, Man-Hon (2010). "Effect of Spatial Locality on an Evolutionary Algorithm for Multimodal Optimization". Applications of Evolutionary Computation. Lecture Notes in Computer Science. Vol. 6024. pp. 481–490. CiteSeerX   10.1.1.655.5490 . doi:10.1007/978-3-642-12239-2_50. ISBN   978-3-642-12238-5.
60. Wong, Ka-Chun; Leung, Kwong-Sak; Wong, Man-Hon (2009). "An evolutionary algorithm with species-specific explosion for multimodal optimization". Proceedings of the 11th Annual conference on Genetic and evolutionary computation. p. 923. doi:10.1145/1569901.1570027. ISBN   978-1-60558-325-9. S2CID   16308189.{{cite book}}: |work= ignored (help)
61. Wong, Ka-Chun; Wu, Chun-Ho; Mok, Ricky K.P.; Peng, Chengbin; Zhang, Zhaolei (2012). "Evolutionary multimodal optimization using the principle of locality". Information Sciences. 194: 138–170. doi:10.1016/j.ins.2011.12.016.
62. Bagchi Tapan P (1999). Multiobjective Scheduling by Genetic Algorithms. Kluwer Academic. ISBN   978-0-7923-8561-5.
63. "Del Moral - Rare events". u-bordeaux1.fr. Archived from the original on 2012-04-23. Retrieved 2011-12-29.
64. "a review article". Archived from the original on 2016-04-29. Retrieved 2011-12-29.
65. "Del Moral - Optimal Control". u-bordeaux1.fr. Archived from the original on 2012-05-08. Retrieved 2011-12-29.
66. BiSNET/e – Distributed Software Systems Group, University of Massachusetts, Boston Archived 2009-06-22 at the Wayback Machine