Solving Very Large Traveling Salesman Problems by SOM Parallelization on Cluster Architectures

Authors:
Hannes Schabauer;Erich Schikuta;Thomas Weishaupl
Affiliations:
University of Vienna, Austria;University of Vienna, Austria;University of Vienna, Austria
Venue:
PDCAT '05 Proceedings of the Sixth International Conference on Parallel and Distributed Computing Applications and Technologies
Year:
2005

Citing 0
Cited 4

The wise experiencing traveling salesman (WETS): introduction to a simple evolutionary solution for the problem

CEC'09 Proceedings of the Eleventh conference on Congress on Evolutionary Computation
An effective particle swarm optimization algorithm embedded in SA to solve the traveling salesman problem

CCDC'09 Proceedings of the 21st annual international conference on Chinese control and decision conference
A comparison of problem decomposition techniques for the FAP

Journal of Heuristics
A novel two-level hybrid algorithm for multiple traveling salesman problems

ICSI'12 Proceedings of the Third international conference on Advances in Swarm Intelligence - Volume Part I

Quantified Score

Hi-index	0.00

Visualization

Abstract

This paper describes how to solve very large Traveling- Salesman Problems heuristically by the parallelization of self-organizing maps on cluster architectures. The used way of parallelizing is a sophisticated Structural Data Parallel approach based on the SPMD model. We distinguish between a non-sophisticated and a sophisticated approach for efficient and simple parallelization of the SOMs.