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Tutorial Details: Parallel Strategies With Genetic Algorithms

Date: Thursday, March 29, 2007, 01:00 pm - 03:00 pm
Location: 585 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 hands-on tutorial will show how genetic algorithms work and will discuss general optimization strategies with GAs. It will also work through a few GA problems using parallel GA optimization routines.

Level: Intermediate
Prerequisites: Basic skills in MPI and Fortran or C