A study of five parallel approaches to a genetic algorithm for the traveling salesman problem
Date
2005
Authors
Eldridge, B. D., author
Roychowdhury, V. P., author
Siegel, H. J., author
Maciejewski, Anthony A., author
Wang, L., author
TSI® Press, publisher
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Abstract
This paper presents a comparative study of five different coarse-grained parallel genetic algorithms (PGAs) using the traveling salesman problem as the case application. All of these PGAs are based on the same baseline serial genetic algorithm, implemented on the same parallel machine (IBM SP2), tested on the same problem instances, and started from the same set of initial populations. Based on these experiments, a 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.
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Subject
parallel genetic algorithms
traveling salesman problem
memetic algorithms