Genetic Algorithms and their applications

This talk will explain what a genetic algorithm is and give two examples of the application of genetic algorithms to real problems. The goal of the talk is to acquaint listeners with the genetic algorithm approach to evolutionary computation and, by example, to give them some idea of what such algorithms can and can not do.

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Table of Contents

Genetic Algorithms and their applications

About Genetic Algorithms

Some selected sources

More selected sources

Genetic Algorithm Cocktail Party Facts

Sociology of the Evolutionary Computation Field

Features of a Genetic Algorithm

Anatomy of a Genetic Algorithm

The population


Example of parent selection


Mutation causes local modification

Crossover causes recombination of genetic material



Sample run of a steady-state GA

New population with a mutation and a crossover

New population with a mutation and a crossover

Comments on this demonstration run of a GA

Domain-based and hybrid GAs

GAs hybridize well with other optimization algorithms

Frequently Asked Questions (1)

Frequently Asked Questions (2)

Some published success: Financial

Some published success: Scheduling

Some published success: Telecommunications

Some published success: Design

Some application areas by domain

Some application areas by technique

How to do this at home, Phase 1

How to do this at home, Phase 2

How to find tools

Author: Lawrence "David" Davis
President, Tica Associates

Lawrence "David" Davis is the President of Tica Associates, a consulting company that he founded in 1990. Tica was the first company to specialize in solving real-world problems with genetic algorithms. Dr. Davis began working with genetic algorithms at Texas Instruments in the early 1980s. He wrote/edited the Handbook of Genetic Algorithms and edited Genetic Algorithms and Simulated Annealing. Dr. Davis helped found the Society for Genetic Algorithms and the journals Evolutionary Computation and Heuristics. He has published more than forty papers, most of them on genetic algorithms and their applications.