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Genetic Algorithms

Overview: Genetic algorithms (GAs) are search procedures that use the mechanics of natural selection and natural genetics. The genetic algorithm, first developed by John H. Holland in the 1960's, allows computers to solve difficult problems. It uses evolutionary techniques, based on function optimization and artificial intelligence, to develop a solution. The basic operation of a genetic algorithm is simple. First a population of possible solutions to a problem are developed. Next, the better solutions are recombined with each other to form some new solutions. Finally the new solutions are used to replace the poorer of the original solutions and the process is repeated.

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Genetic Algorithms Information on the Internet
CMU Genetic Algorithms Index Genetic algorithms and genetic programming, archives for the comp.ai.genetic newsgroup, FAQ, papers, and source code for genetic programming examples. 
Gaucsd Genetic algorithm package (HP-UX 8.07 Source Code). 
Genetic Algorithms (GA) Archive The Genetic Algorithms Archive includes past issues of the GA-digest, source code for many GA implementations, and announcements about GA-related conferences. Links to sites around the world with material related to evolutionary computation. The second directory contains source code for GA. 
Genetic Algorithms FAQ Genetic algorithms and genetic programming, archives for the comp.ai.genetic newsgroup. 
Genetic Algorithms FAQ Genetic algorithms and genetic programming, archives for the comp.ai.genetic newsgroup, papers, and source code for genetic programming examples. 
Genetic-Programming.org - Home Page Information about the field of genetic programming. Includes information on genetic programming conferences.
The Genetic Programming Notebook Information on a variety of topics within genetic programming, genetic algorithms, and artificial intelligence.
Illinois Genetic Algorithms Laboratory Study the fundamental problem solving approach of nature which is evolution. Includes several publications order forms and a site link list. 
Messy Genetic Algorithm (LISP) Files This directory contains the files for the messy GA (mGA) LISP code documented in the technical report "mGA 1.0: A Common LISP Implementation of a Messy Genetic Algorithm (TCGA Report No. 90004, by David E. Goldberg and T. Kerzic, 1990). 
Miscellaneous Genetic Algorithms Files FTP archive for Genetic Algorithms related files. 
Miscellaneous Genetic Algorithms Files References to Genetic Algorithms related programs at the Santa Fe Institute. 
Will's Technical Page A collection of articles and other technical resources for artificial intelligence (especially data mining and machine learning).
Yahoo - Genetic Algorithms Programming Language Links to the genetic algorithms archive, bibliography, institute list, and an archive of FAQs. 

Sponsors of PC AI - Genetic Algorithms Vendors
Specializes in biologically-based computer systems for business and science that learn, adapt and evolve. In a world of accelerating change, systems and solutions must be able to adapt quickly. We build systems that are based upon dynamic natural processes. These powerful solutions are increasingly a part of strategic and tactical systems throughout the world.
Provider of multi-strategy data mining suite PolyAnalyst features a hybrid Genetic Algorithm-Memory Based Reasoning exploration engine as one of many available algorithms.
QMC provides an advanced generation of PC-based software technologies that interpret, analyze, and configure data for any process in any industry.

Other Genetic Algorithms Vendors
American Heuristics Corporation AHC is a technology transfer company that specializes in the research and development of advanced software technologies and their application to complex technical problems. 
Attar Software Authors of the XpertRule range of software for Knowledge-based development, resource optimization, and data mining. (info@attar.com) 
The primary objective of Flexible Intelligence Group, LLC. (FIG) is to design, develop, and market independent modules which may be used, in isolation or in combination with systems, to (a) provide computational intelligence to a system or (b) improve the computational intelligence of a system. At present, this requires the development of soft computing modules that integrates techniques such as fuzzy systems, evolutionary algorithms, neural networks, and chaos theory . 
Gordian Institute A division of American Heuristics Corporation whose mission is to facilitate the transfer of new technologies through first-rate, hands-on, intensive training courses. New courses are added to the curriculum as advancing technologies become sufficiently mature to warrant commercial attention. 
Man Machine Interfaces  None at this time 
OptiGA - Genetic Algorithms ActiveX Control ActiveX control for the implementation of genetic algorithms.
Palisade Corporation Palisade Corporation produces many analytical power tools, including Evolver 4.0 and @Risk. Evolver 4.0 uses genetic algorithms to solve complex optimization problems. @Risk ads Monte Carlo simulation directly into Microsoft Project.
Predictive Dynamix, Inc. Predictive Dynamix provides a comprehensive suite of software tools for commercial data mining applications
RoboWiz Corporation  (pdfisk@ibm.net) (75253.3274@compuserve.com) 
The Schwartz Associates  tjs333@juno.com www.zoom.com/tsa 
Ward Systems Group, Inc. is a progressive company that transforms the latest developments in neural networks and artificial intelligence into pratical problem solving tools for the business, scientific, and academic environments. The company was established in 1988 and has over seven years experience in assisting customers on creating neural networks. Learn about the AI Trilogy. 
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Article References
Ask the Expert: Hottest "New" Technologies Give Lie To High-tech Beliefs  Shafer, D. (1991) PC AI, 5(4), 18-19. 
Review: MicroGA: Exploring Genetic Algorithms  Darling, C. (1994) PC AI, 8(2) , 44-46. 
Genehunter: GA Software From Ward  Lewinson, L. (1995) PC AI, 9(2) , 26. 
Genetic Algorithms  Hill, R. (1996) PC AI, 10(3) , 27.
Genetic Algorithms at Work: Two Case Studies  Lipton, M.J., Rosenof, H.P., and Liston, G. (1996) PC AI, 10(5) , 16. 
Genetic Algorithms in Battlefield Communications  Chang, T. (1997) PC AI, 11(5) , 28. 
Data Mining, Modeling, Simulation and Genetic Algorithms in the Chemical Process Industries van Buskirk, P. (1999) PC AI, 13(5), 28
Tackling Real-World Environmental Engineering Challenges with Linear Genetic Programming Deschaine, L. (2000) PC AI, 14(5), 35

Book References
Machine Learning: Neural Networks, Genetic Algorithms, and Fuzzy Systems  Adeli, H. and Hung, S. (1995) New York, NY: John Wiley & Sons Inc, pps. 211. ISBN: 0-471-01633-0. 
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Practical Genetic Algorithms Haupt, R. and Haupt. S. (1998) John Wiley & Sons, pps. 192. ISBN 0471188735
Adaptive Learning by Genetic Algorithms : Analytical Results and Applications to Economic Models David, H. (1999) Springer Verlag, pps. 200. ISBN 3540656073
Evolutionary Algorithms in Engineering and Computer Science : Recent Advances in Genetic Algorithms, Evolution Strategies, Evolutionary Programming . . . Miettinen, K.; Neittaanmaki, P.; Periaux, J. (1999) John Wiley & Sons Ltd., pps. 483. ISBN 0471999024
The Practical Handbook of Genetic Algorithms: Applications, Second Edition Chambers, L. (ed.) (2000) CRC Press, pps. 528. ISBN 1584882409
Genetic Algorithms and Engineering Optimization (Wiley Series in Engineering Design and Automation) Gen, M. and Cheng, R. (2000) John Wiley & Sons, pps. 512. ISBN 0471315311
Evolutionary Algorithms : The Role of Mutation and Recombination (Natural Computing Series) Spears, W. (2000) Springer Verlag, pps. 245. ISBN 3540669507

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