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Parallel ACO with a Ring Neighborhood for Dynamic TSP

Parallel ACO with a Ring Neighborhood for Dynamic TSP

Camelia M. Pintea, Gloria Cerasela Crisan, Mihai Manea
Copyright: © 2012 |Volume: 5 |Issue: 4 |Pages: 13
ISSN: 1938-7857|EISSN: 1938-7865|EISBN13: 9781466615045|DOI: 10.4018/jitr.2012100101
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MLA

Pintea, Camelia M., et al. "Parallel ACO with a Ring Neighborhood for Dynamic TSP." JITR vol.5, no.4 2012: pp.1-13. http://doi.org/10.4018/jitr.2012100101

APA

Pintea, C. M., Crisan, G. C., & Manea, M. (2012). Parallel ACO with a Ring Neighborhood for Dynamic TSP. Journal of Information Technology Research (JITR), 5(4), 1-13. http://doi.org/10.4018/jitr.2012100101

Chicago

Pintea, Camelia M., Gloria Cerasela Crisan, and Mihai Manea. "Parallel ACO with a Ring Neighborhood for Dynamic TSP," Journal of Information Technology Research (JITR) 5, no.4: 1-13. http://doi.org/10.4018/jitr.2012100101

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Abstract

The current paper introduces a new parallel computing technique based on ant colony optimization for a dynamic routing problem. Ant Colony Optimization is a metaheurisitc that is able to solve large scale optimization problems. In the dynamic traveling salesman problem, the distances between cities as travel times are no longer fixed. The new technique uses a parallel model for a problem variant that allows a slight movement of nodes within their neighborhoods. The algorithm is tested with success on several large data sets. The paper concludes with a discussion of the results provided by both the sequential and parallel approaches and calls for further research on the subject.

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