JSM 2004 - Toronto

Abstract #300067

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Activity Number: 253
Type: Invited
Date/Time: Tuesday, August 10, 2004 : 2:00 PM to 3:50 PM
Sponsor: Business and Economics Statistics Section
Abstract - #300067
Title: An Overview of Genetic Algorithms and Their Applications
Author(s): Sangit Chatterjee*+
Companies: Northeastern University
Address: 219 Hayden Hall, Boston, MA, 02130,
Keywords: binary digits ; stochastic optimization ; evolutionary operators ; natural selection ; statistical modeling
Abstract:

Genetic Algorithms (GA) are stochastic optimization tools that work on Darwinian models of population biology and are capable of solving for near-optimal solution for multivariable functions without the usual mathematical requirements of strict continuity, differentiability, convexity, and other properties. A GA typically begins by randomly choosing a number of candidate solutions which propagate themselves through a "selection criteria" and are changed by genetic operators. Gas have seen some statistical applications and have been used to solve discrete optimization problems with a considerable degree of success. This talk will give a very broad outline of genetic algorithms and an even broader view of its applications potential. Some difficulties, limitations, and open questions will conclude the talk.


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Revised March 2004