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A study of five parallel approaches to a genetic algorithm for the traveling salesman problem

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dc.contributor.authorEldridge, B. D., author
dc.contributor.authorRoychowdhury, V. P., author
dc.contributor.authorSiegel, H. J., author
dc.contributor.authorMaciejewski, Anthony A., author
dc.contributor.authorWang, L., author
dc.contributor.authorTSI® Press, publisher
dc.date.accessioned2007-01-03T08:09:34Z
dc.date.available2007-01-03T08:09:34Z
dc.date.issued2005
dc.description.abstractThis 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.
dc.format.mediumborn digital
dc.format.mediumarticles
dc.identifier.bibliographicCitationWang, L., et al., A Study of Five Parallel Approaches to a Genetic Algorithm for the Traveling Salesman Problems, Intelligent Automation and Soft Computing 11, no. 4 (2005): 217-234.
dc.identifier.urihttp://hdl.handle.net/10217/67367
dc.languageEnglish
dc.language.isoeng
dc.publisherColorado State University. Libraries
dc.relation.ispartofFaculty Publications
dc.rights©2005 TSI® Press.
dc.rightsCopyright 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.
dc.subjectparallel genetic algorithms
dc.subjecttraveling salesman problem
dc.subjectmemetic algorithms
dc.titleA study of five parallel approaches to a genetic algorithm for the traveling salesman problem
dc.typeText

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