Roychowdhury, Vwani P., authorSiegel, Howard Jay, authorMaciejewski, Anthony A., authorWang, Lee, authorIEEE, publisher2007-01-032007-01-031998Wang, Lee, et al., A Comparative Study of Five Parallel Genetic Algorithms Using the Traveling Salesman Problem, Proceedings of the First Merged International Parallel Processing Symposium & Symposium on Parallel and Distributed Processing, March 30-April 3, 1998, Orlando, Florida: 345-349.http://hdl.handle.net/10217/1221Parallel genetic algorithms (PGAs) have been developed to reduce the large execution times that are associated with serial genetic algorithms (SGAs). They have also been used to solve larger problems and to find better solutions. In this paper, a comparative analysis of five different coarse-grained PGAs is conducted using the traveling salesman problem as the basis of this case study. To make fair comparisons, all of these PGAs are based on the same baseline SGA, implemented on the same parallel machine (IBM SP2), tested on the same set of traveling salesman problem instances, and started from the same set of initial populations. As a result of the experiments conducted in this study, a particular PGA that combines a new subtour technique with a known migration approach is identified to be the best for the traveling salesman problem among the five PGAs being compared.born digitalproceedings (reports)eng©1998 IEEE.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.travelling salesman problemsparallel algorithmsgenetic algorithmsText