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Tutorial Details: Optimizing with Genetic Algorithms

Date: Thursday, February 23, 2006, 01:00 pm - 03:00 pm
Location: 402 Walter
Instructor(s): Benjamin J. Lynch, MSI

Many scientific problems require the optimization of multidimensional functions that have dozens or even thousands of local minima and maxima. Local optimization methods such as the Newton-Raphson method and its many variants can find nearby local extrema but have little or no chance of finding a global minimum or maximum. Using a genetic algorithm (GA) is often a very efficient means to find a global minimum or maximum for complex functions.

This tutorial will describe how genetic algorithms work and we will discuss general optimization strategies with GAs. We will also discuss a few GA programs available and how one might parallelize a GA optimization.

Level:
Prerequisites: Calculus and UNIX knowledge helpful, but not necessary