John Holland developed genetic algorithms in the 1960s while working at the University of Michigan. Genetic algorithms are inspired by Darwinian evolution and use operations like selection, crossover and mutation to evolve solutions to problems. They work by encoding potential solutions into bit strings and manipulating them to find better solutions over time. Most commercial solvers now use evolutionary algorithms based on Holland's genetic algorithm work.

1. Universidad San Carlos de Guatemala Facultad de Ingeniería

2. Basics Links

3. John Holland and The Nature 1950 contact with Computers 1960 start in University of Michigan and the Logic of computers group Reading Genetic Theory of Natural Selection by R. A. Fisher Adaptative Systems Theory (Course)

4. To imitate the Adaptative natural systems process Design of Artificial systems that keep functions as Natural Systems

5. Holland’s Student Industrial Engineer Pipelines GA Design using Apple II ICGA´85.

6. A genetic or evolutionary algorithm applies the principles of evolution found in nature to the problem of finding an optimal solution to a Solver problem. In a "genetic algorithm," the problem is encoded in a series of bit strings that are manipulated by the algorithm; in an "evolutionary algorithm," the decision variables and problem functions are used directly. Most commercial Solver products are based on evolutionary algorithms.

7. Industrial Engineers Chemical Engineers Informatics Engineers

8. http://geneura.ugr.es/~jmerelo/ie/ags.htm http://www.solver.com/gabasics.htm VIDEO Estudiante 1 VIDEO Estudiante 2

9. Javier Gramajo López [email_address] http://jgramajo.wordpress.com/ http://www.youtube.com/jgramajo/ http://jgramajo.podcastpeople.com/