Siegel, Howard Jay, authorBraun, Tracy D., authorTheys, Mitchell D., authorMaciejewski, Anthony A., authorJohn Wiley & Sons, Inc., publisher2007-01-032007-01-032001Theys, Mitchell D., et al., Mapping Tasks onto Distributed Heterogeneous Computing Systems Using a Genetic Alogrithm Approach, Zomaya, Albert Y., Fikret Ercal, and Stephan Olariu, eds. Solutions to Parallel and Distributed Computing Problems: Lessons from Biological Sciences, 135-178. New York: John Wiley & Sons, Inc, 2001.http://hdl.handle.net/10217/67397Much work has been done using GAs of various types to solve the problem of matching and scheduling of tasks and meta-tasks in a mixed-machine distributed, heterogeneous computing environment. This chapter has discussed three types of genetic algorithms that have been studied to solve this problem. Each implementation has particular specifications and qualifications that were being met. In all cases, the genetic algorithm proved to be a useful method for solving the making and scheduling problem being researched.born digitalchapter titleseng©2001 John Wiley & Sons, Inc.Copyright and other restrictions may apply. User is responsible for compliance with all applicable laws. For information about copyright law, please see https://libguides.colostate.edu/copyright.Text