Tutorial Details: Optimizing with Genetic Algorithms
|Date:||Thursday, February 23, 2006, 01:00 pm - 03:00 pm|
|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.
|Prerequisites:||Calculus and UNIX knowledge helpful, but not necessary|