Tutorial Details: Optimizing with Genetic Algorithms
|Date:||Monday, March 7, 2005, 01:00 pm - 03:00 pm|
|Location:||Room 405 Walter|
|Instructor(s):||Benjamin J. Lynch, MSI|
Many scientific problems require the optimization of complex functions that have dozens or even thousands of local minima and maxima. Local optimization methods such as Newton-Raphson 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|