Abstract
This paper presents a combination of a parallel Genetic Algorithm (GA) and a local search methodology for the Steiner Problem in Networks (SPN). Several previous papers have proposed the adoption of GAs and others metaheuristics to solve the SPN demonstrating the validity of their approaches. This work differs from them for two main reasons: the dimension and the features of the networks adopted in the experiments and the aim from which it has been originated. The reason that aimed this work was namely to assess deterministic and computationally inexpensive algorithms which can be used in practical engineering applications, such as the multicast transmission in the Internet. The large dimensions of our sample networks require the adoption of an efficient grid based parallel implementation of the Steiner GAs. Furthermore, a local search technique, which complements the global search capability of the GA, is implemented by means of a heuristic method. Finally, a further mutation operator is added to the GA replacing the original genome with the solution achieved by the heuristic, providing thus a mechanism like the genetically modified organisms in nature. Although the results achieved cannot be applied directly to the problem we investigate, they can be used to validate other methodologies that can find better applications in the telecommunication field.
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Kruskal, J.: On the Shortest Spanning Subtree of a Graph and the Traveling Salesman Problem. Proc. Amer. Math. Soc. 7, 48–50 (1956)
Karp, R.M.: Reducibility among Combinatorial Problems. In: R.E. Miller, J.W. Thatcher, Complexity of Computer Computations, pp. 85–103. Plenum Press, New York (1972)
Takahashi, H., Matsuyama, A.: An approximate solution for the Steiner problem in graphs. Math. Japan, 573–577 (1980)
Rayward-Smith, V.J.: The computation of nearly minimal Steiner trees in graphs. Int. Math. Ed. Sci. Tech. 14, 15–23 (1983)
Winter, P.: Steiner problem in networks: a survey. Networks 17, 129–167 (1987)
Goldberg, D.E.: Genetic algorithm in Search, Optimization, and Machine Learning. Addison Wesley, Reading (1989)
Dowsland, K.A.: Hill-climbing, Simulated Annealing and the Steiner Problem in Graphs. Engineering Optimisation 17, 91–107 (1991)
Cantu-Paz, E.: A summary of research on parallel genetic algorithms, Illinois GALab, Univ. Illinois Urbana-Champaign, Urbana, IL, Tech. Rep. 950076 (July 1995)
Esbensen, H.: Computing Near-Optimal Solutions to the Steiner Problem in a Graph Using a Genetic Algorithm. Networks: An International Journal 26 (1995)
Gendreau, M., Larochelle, J.F., Sanso, B.: A Tabu Search Heuristic for the Steiner Tree Problem. Networks 34, 162–172 (1999)
Di Fatta, G., Lo Re, G.: Efficient tree construction for the multicast problem, Special issue of the Journal of the Brazilian Telecommunications Society (1999)
Govindan, R., Tangmunarunkit, H.: Heuristics for Internet Map Discovery. In: Proc. IEEE Infocom 2000, Tel Aviv, Israel (2000), www.isi.edu/scan/mercator/mercator.html
Voss, S., Martin, A., Koch, T.: SteinLib Testdata Library (February 2001), elib.zib.de/steinlib/steinlib.php
Medina, A., Lakhina, A., Matta, I., Byers, J.: BRITE Topology Generator (April 2001), cs-pub.bu.edu/brite
Folino, G., Pizzuti, C., Spezzano, G.: Parallel Hybrid Method for SAT That Couples Genetic Algorithms and Local Search. IEEE Transactions on Evolutionary Computation 5(4), 323–334 (2001)
Karonis, N., Toonen, B., Foster, I.: MPICH-G2: A Grid-Enabled Implementation of the Message Passing Interface. Journal of Parallel and Distributed Computing (JPDC) 63(5), 551–563 (2003)
Di Fatta, G., Lo Presti, G., Lo Re, G.: A Parallel Genetic Algorithm for the Steiner Problem in Networks. In: Proc. of the 15th IASTED Int. Conference on Parallel and Distributed Computing and Systems, Marina del Rey (CA), USA (November 2003)
GAlib: a C++ Library of Genetic Algorithm Components, http://lancet.mit.edu/ga/
Sandholm, T., Gawor, J.: Globus Toolkit 3 Core – A Grid Service Container Framework, http://www-unix.globus.org/toolkit/3.0/ogsa/docs/gt3core.pdf
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Presti, G.L., Re, G.L., Storniolo, P., Urso, A. (2004). A Grid Enabled Parallel Hybrid Genetic Algorithm for SPN. In: Bubak, M., van Albada, G.D., Sloot, P.M.A., Dongarra, J. (eds) Computational Science - ICCS 2004. ICCS 2004. Lecture Notes in Computer Science, vol 3036. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-540-24685-5_20
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DOI: https://doi.org/10.1007/978-3-540-24685-5_20
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