List of genetic algorithm applications

This is a list of Genetic Algorithm (GA) applications

Applications of genetic algorithms

• Airlines Revenue Management.^[1]
• Artificial creativity
• Audio watermark insertion/detection
• Automated design = computer-automated design
• 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 of sophisticated trading systems in the financial sector.
• Automated design, including research on composite material design and multi-objective design of automotive components for crashworthiness, weight savings, and other characteristics.
• Bayesian inference ([2] links to particle methods in Bayesian statistics and hidden Markov chain models and [3] a tutorial on genetic particle models)
• Bioinformatics multiple sequence alignment.^[2]
• Bioinformatics: RNA structure prediction.^[3]
• Bioinformatics: Multiple Sequence Alignment.^[4] SAGA is available on:.^[5]
• Bioinformatics: Motif Discovery.^[6]
• Biology and computational chemistry ([4] links to particle methods in biology and computational chemistry and [5] an article on genetic particle models)
• Building phylogenetic trees.^[7]
• Calculation of bound states and local-density approximations.
• Chemical kinetics (gas and solid phases)
• Clustering. Using genetic algorithms to optimize a wide range of different fit-functions.^{[dead link][8]}
• Code-breaking, using the GA to search large solution spaces of ciphers for the one correct decryption.^[9]
• Computer architecture: using GA to find out weak links in approximate computing such as look-ahead.
• Computer-automated design ^[10]
• 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.^[11]
• Container loading optimization.
• Control engineering,.^{[12][13][14][15]}
• Data Center/Server Farm.^[16]
• Design of water distribution systems.
• Distributed computer network topologies.
• Electronic circuit design, known as evolvable hardware.
• Gene expression profiling analysis.^[17]
• Feynman-Kac models ([6] links to genetic type particle interpretations, [7] a review article on genetic particle models, and a research monograph [8])
• Financial Mathematics ([9] links to particle methods in mathematical finance and [10] a tutorial on genetic particle models)
• File allocation for a distributed system.
• Filtering and signal processing ([11] links to particle filters and [12] a tutorial on genetic particle models)
• Finding hardware bugs.^[18][19]
• Game theory equilibrium resolution.
• Genetic Algorithm for Rule Set Production
• Economics
• Scheduling applications, including job-shop scheduling and scheduling in printed circuit board assembly.^[20] 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.
• Groundwater monitoring networks^[21]
• Learning robot behavior using genetic algorithms.
• Image processing: Dense pixel matching.^[22]
• Learning fuzzy rule base using genetic algorithms.
• Linguistic analysis, including grammar induction and other aspects of Natural language processing (NLP) such as word sense disambiguation.
• Marketing mix analysis
• Mechanical engineering^[23][24]
• Mobile communications infrastructure optimization.
• Molecular structure optimization (chemistry).
• Multidimensional systems
• Multimodal Optimization ^[25][26][27]
• Multiple criteria production scheduling.^[28]
• Multiple population topologies and interchange methodologies.
• Mutation testing
• Neural Networks; particularly recurrent neural networks^[29]
• Operon prediction.^[30]
• Optimisation of data compression systems, for example using wavelets.
• Parallelization of GAs/GPs including use of hierarchical decomposition of problem domains and design spaces nesting of irregular shapes using feature matching and GAs.
• Plant floor layout.
• Pop music record producer.^[31]
• Power electronics design.^[32]
• Protein folding and protein/ligand docking.^[33][34]
• Quality control
• Rare event analysis ([13] links to particle rare event simulation and [14] a review article)
• Representing rational agents in economic models such as the cobweb model.
• Selection of optimal mathematical model to describe biological systems.
• Software engineering ^{[citation needed]}
• Solving the machine-component grouping problem required for cellular manufacturing systems.
• Stochastic optimization ([15] links to particle methods in regulation, optimization, and optimal control)
• Tactical asset allocation and international equity strategies.
• Timetabling problems, such as designing a non-conflicting class timetable for a large university.
• Training artificial neural networks when pre-classified training examples are not readily obtainable (neuroevolution).
• Traveling salesman problem and its applications.^[20]
• Vehicle routing problems with multiple soft time windows, multiple depots and an heterogeneous fleet
• Wireless sensor/ad-hoc networks.^[35]

References

1. Aloysius George, B. R. Rajakumar, D. Binu,(2012) "Genetic algorithm based airlines booking terminal open/close decision system". [1]
2. Gondro C, Kinghorn BP (2007). "A simple genetic algorithm for multiple sequence alignment". Genetics and Molecular Research. 6 (4): 964–982. PMID 18058716.
3. 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. doi:10.1006/jtbi.1995.0098. PMID 7545258.
4. 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.
5. Cedric Notredame Home Page
6. Ka-Chun Wong*, Chengbin Peng, Man-Hon Wong, Kwong-Sak Leung: Generalizing and learning protein-DNA binding sequence representations by an evolutionary algorithm. Soft Computing, 15:1631-1642, 2011.
7. Hill T, Lundgren A, Fredriksson R, Schiöth HB (2005). "Genetic algorithm for large-scale maximum parsimony phylogenetic analysis of proteins". Biochimica et Biophysica Acta. 1725 (1): 19–29. doi:10.1016/j.bbagen.2005.04.027. PMID 15990235.
8. 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
9. Joachim De Zutter
10. Li, Y., et al. (2004). CAutoCSD – Evolutionary search and optimisation enabled computer automated control system design. International Journal of Automation and Computing, 1(1). pp. 76–88. ISSN 1751-8520, http://eprints.gla.ac.uk/3818/
11. Craig Aaen Stockdale (June 1, 2008). "A (r)evolution in Crime-fighting". Forensic Magazine.
12. Ng, K.C., Switching Control Systems and Their Design Automation via Genetic Algorithms, PhD Thesis, University of Glasgow, 1995.
13. Li, Y.; et al. (1996). "Genetic algorithm automated approach to design of sliding mode control systems". Int J Control. 63 (4): 721–739. doi:10.1080/00207179608921865. CiteSeer^x: 10.1.1.43.1654 . {{cite journal}}: Explicit use of et al. in: |author2= (help)
14. K. Michail, Optimised Configuration of Sensing Elements for Control and Fault Tolerance Applied to an Electro-Magnetic Suspension, PhD Thesis, Loughborough University, UK, 2009.
15. Patrascu, M. (2015). "Genetically enhanced modal controller design for seismic vibration in nonlinear multi-damper configuration". Proc.I.Mech. Part I: Journal of Systems and Control Engineering. 229 (2): 158–168.
16. SymbioticSphere – Distributed Software Systems Group, University of Massachusetts, Boston
17. 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.
18. Hitoshi Iba, Sumitaka Akiba, Tetsuya Higuchi, Taisuke Sato: BUGS: A Bug-Based Search Strategy using Genetic Algorithms. PPSN 1992:
19. Ibrahim, W. and Amer, H.: An Adaptive Genetic Algorithm for VLSI Test Vector Selection
20. Maimon, Oded; Braha, Dan (1998). "A genetic algorithm approach to scheduling PCBs on a single machine" (PDF). International Journal of Production Research. 36: 3.
21. Optimization of Water-level Monitoring Networks in the Eastern Snake River Plain Aquifer Using a Kriging-based Genetic Algorithm Method United States Geological Survey
22. 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
23. "Genetic Algorithms for Engineering Optimization" (PDF).
24. "Applications of evolutionary algorithms in mechanical engineering".
25. Ka-Chun Wong, Kwong-Sak Leung, Man Hon Wong: Effect of Spatial Locality on an Evolutionary Algorithm for Multimodal Optimization. EvoApplications (1) 2010: 481-490
26. Ka-Chun Wong, Kwong-Sak Leung, Man Hon Wong: An evolutionary algorithm with species-specific explosion for multimodal optimization. GECCO 2009: 923-930
27. Ka-Chun Wong, Chun-Ho Wu, Ricky K.P. Mok, Chengbin Peng, Zhaolei Zhang, Evolutionary multimodal optimization using the principle of locality, Information Sciences, Volume 194, 1 July 2012, Pages 138-170, ISSN 0020-0255, 10.1016/j.ins.2011.12.016
28. Bagchi Tapan P (1999). "Multiobjective Scheduling by Genetic Algorithms". Multiobjective Scheduling by Genetic Algorithms. Kluwer Academic. ISBN 0-7923-8561-6.
29. Applying Genetic Algorithms to Recurrent Neural Networks for Learning Network Parameters and Architecture
30. 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.
31. "To the beat of the byte". BBC News. 1998-07-01. Retrieved 2010-05-03.
32. Zhang, J., Lo, W.L., and Chung, H., "Pseudocoevolutionary Genetic Algorithms for Power Electronic Circuits Optimization", IEEE Trans Systems, Man, and Cybernetics, Part C., Vol.36, No.4, July 2006, pp. 590–598.
33. 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.
34. Wong, K., Leung, K., and Wong, M. 2010. Protein structure prediction on a lattice model via multimodal optimization techniques. GECCO 2010: 155-162
35. BiSNET/e – Distributed Software Systems Group, University of Massachusetts, Boston