List of genetic algorithm applications: Difference between revisions
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This is a list of Genetic Algorithm (GA) applications
Applications of genetic algorithms
- Artificial creativity
- Audio watermark 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.
- Bioinformatics multiple sequence alignment.[1]
- Bioinformatics: RNA structure prediction.[2]
- Bioinformatics: [Multiple Sequence Alignment].[3] SAGA is available on:[4] .
- Building phylogenetic trees.[5]
- Calculation of bound states and local-density approximations.
- Chemical kinetics (gas and solid phases)
- Code-breaking, using the GA to search large solution spaces of ciphers for the one correct decryption.[6]
- Computer-automated design [7]
- Configuration applications, particularly physics applications of optimal molecule configurations for particular systems like C60 (buckyballs).
- Container loading optimization.
- Control engineering [8],[9].[10]
- Data Center/Server Farm.[11]
- Design of water distribution systems.
- Distributed computer network topologies.
- Electronic circuit design, known as evolvable hardware.
- Gene expression profiling analysis.[12]
- File allocation for a distributed system.
- Finding hardware bugs.[13][14]
- Game theory equilibrium resolution.
- Genetic Algorithm for Rule Set Production
- Economics
- Scheduling applications, including job-shop scheduling. 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.
- Learning robot behavior using genetic algorithms.
- 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
- Mobile communications infrastructure optimization.
- Molecular structure optimization (chemistry).
- Multidimensional systems
- Multimodal Optimization [15][16]
- Multiple criteria production scheduling.[17]
- Multiple population topologies and interchange methodologies.
- Mutation testing
- Neural Networks; particularly recurrent neural networks[18]
- Operon prediction.[19]
- 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.[20]
- Power electronics design[21].
- Protein folding and protein/ligand docking.[22][23]
- Quality control
- 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.
- 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.
- Wireless sensor/ad-hoc networks.[24]
See also
References
- ^ Gondro C, Kinghorn BP (2007). "A simple genetic algorithm for multiple sequence alignment". Genetics and Molecular Research. 6 (4): 964–982. PMID 18058716.
- ^ 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.
{{cite journal}}: CS1 maint: multiple names: authors list (link) - ^ Notredame C, Higgins DG (1995). "SAGA a Genetic Algorithm for Multiple Sequence Alignment". Nulceic Acids Research. 174 (8): 1515. PMC 145823. PMID 8628686.
- ^ Cedric Notredame Home Page
- ^ 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.
{{cite journal}}: CS1 maint: multiple names: authors list (link) - ^ Joachim De Zutter
- ^ 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/
- ^ Ng, K.C., Switching Control Systems and Their Design Automation via Genetic Algorithms, PhD Thesis, University of Glasgow, 1995.
- ^ Li, Y., et al. (1996). Genetic algorithm automated approach to design of sliding mode control systems, Int J Control, 63(4), 721–739.
- ^ K. Michail, Optimised Configuration of Sensing Elements for Control and Fault Tolerance Applied to an Electro-Magnetic Suspension, PhD Thesis, Loughborough University, UK, 2009.
- ^ SymbioticSphere – Distributed Software Systems Group, University of Massachusetts, Boston
- ^ 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.
{{cite journal}}: CS1 maint: unflagged free DOI (link) - ^ Hitoshi Iba, Sumitaka Akiba, Tetsuya Higuchi, Taisuke Sato: BUGS: A Bug-Based Search Strategy using Genetic Algorithms. PPSN 1992:
- ^ Ibrahim, W. and Amer, H.: An Adaptive Genetic Algorithm for VLSI Test Vector Selection
- ^ 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
- ^ Ka-Chun Wong, Kwong-Sak Leung, Man Hon Wong: An evolutionary algorithm with species-specific explosion for multimodal optimization. GECCO 2009: 923-930
- ^ Bagchi Tapan P (1999). "Multiobjective Scheduling by Genetic Algorithms". Multiobjective Scheduling by Genetic Algorithms.
{{cite journal}}: Text "Kluwer Academic. ISBN 0-7923-8561-6" ignored (help) - ^ Applying Genetic Algorithms to Recurrent Neural Networks for Learning Network Parameters and Architecture
- ^ 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.
{{cite journal}}: CS1 maint: multiple names: authors list (link) - ^ "To the beat of the byte". BBC News. 1998-07-01. Retrieved 2010-05-03.
- ^ 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.
- ^ 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.
- ^ Wong, K., Leung, K., and Wong, M. 2010. Protein structure prediction on a lattice model via multimodal optimization techniques. GECCO 2010: 155-162
- ^ BiSNET/e – Distributed Software Systems Group, University of Massachusetts, Boston