Solving Euclidean Steiner Tree Problems with Multi Swarm Optimization
Pages 1379 - 1380
Abstract
A new iterative heuristic algorithm, based on Multi Swarm Optimization, is presented for Steiner Tree Problems (STP) in the 2-dimensional Euclidean plane. The basic algorithm is made practical for large instances by applying a result from graph theory, and a well-informed approximation. The algorithm's performance is compared to perfect solutions for the classic Steiner Tree Problem and to a deterministic heuristic for the k-bottleneck STP, a variant of STP. The algorithm often produces near optimal solutions with limited resources. The approach can be applied to higher dimensions and to other variants of the Steiner Tree Problem.
References
[1]
Marcus Brazil, Charl Ras, and Doreen Thomas. A new algorithm for the euclidean k-bottleneck steiner problem. In Proceedings of the 19th International Symposium on Mathematical Theory of Networks and Systems-MTNS, volume 5, 2010.
[2]
James Kennedy. Particle swarm optimization. In Encyclopedia of Machine Learning, pages 760--766. Springer, 2010.
[3]
L. Wang and D.-Z. Du. Approximations for a bottleneck steiner tree problem. Algorithmica, 32(4):554--561, 2002.
[4]
P. Winter and M. Zachariasen. Large Euclidean Steiner Minimum Trees in an Hour. Rapport (Københavns universitet. Datalogisk institut). Datalogisk Institut, Københavns Universitet, 1996.
Index Terms
- Solving Euclidean Steiner Tree Problems with Multi Swarm Optimization
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July 2015
1568 pages
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Association for Computing Machinery
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Publication History
Published: 11 July 2015
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- Belgian Science Policy Office in the Interuniversity Attraction Pole COMEX
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GECCO '15
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