Abstract
In the recent years an increasing number of computational grids have been built, providing an unprecedented amount of computational power. Based on their inherent parallelism, Evolutionary Algorithms are well suited for distributed execution in such grids. Unfortunately, there are several challenges concerning the usage of a grid infrastructure (e.g. the synchronization and submission of jobs and file transfer tasks). In this paper we present a new framework which makes a Globus based grid easily accessible for Evolutionary Algorithms and takes care of the parallelization. The usability is demonstrated by the example of an Evolutionary Algorithm for the Traveling Salesman Problem.
This is a preview of subscription content, log in via an institution to check access.
Access this chapter
Tax calculation will be finalised at checkout
Purchases are for personal use only
Preview
Unable to display preview. Download preview PDF.
Similar content being viewed by others
References
Goldberg, D.E.: Genetic Algorithms in Search, Optimization, and Machine Learning. Addison-Wesley, Reading (1989)
Alba, E., Troya, J.M.: A Survey of Parallel Distributed Genetic Algorithms. Complexity 4, 31–52 (1999)
Talbi, E.-G., Mostaghim, S., Okabe, T., Ishibuchi, H., Rudolph, G., Coello, C.A.C.: Parallel Approaches for Multiobjective Optimization. In: Branke, J., Deb, K., Miettinen, K., Słowiński, R. (eds.) Multiobjective Optimization. LNCS, vol. 5252, pp. 249–372. Springer, Heidelberg (2009)
Cahon, S., Melab, N., Talbi, E.-G.: ParadisEO: A Framework for the Reusable Design of Parallel and Distributed Metaheuristics. Journal of Heuristics 10(3), 357–380 (2004)
Wall, M.: GAlib: A C++ Library of Genetic Algorithm Components, Massachusetts Institute of Technology, http://lancet.mit.edu/ga/dist/galibdoc.pdf
JGAP - Java Genetic Algorithms Package, http://jgap.sourceforge.net/
Arenas, M.G., Collet, P., Eiben, A.E., Jelasity, M., Merelo, J.J., Paechter, B., Preuß, M., Schoenauer, M.: A Framework for Distributed Evolutionary Algorithms. In: Guervós, J.J.M., Adamidis, P.A., Beyer, H.-G., Fernández-Villacañas, J.-L., Schwefel, H.-P. (eds.) PPSN 2002. LNCS, vol. 2439, pp. 665–675. Springer, Heidelberg (2002)
Foster, I., Kesselman, C.: The Grid: Blueprint for a New Computing Infrastructure. Morgan Kaufmann, San Francisco (1999)
A Globus Primer - Or, Everything You Wanted to Know about Globus, but Were Afraid To Ask, http://www.globus.org/toolkit/docs/4.0/key/GT4_Primer_0.6.pdf
Cahon, S., Melab, N., Talbi, E.-G.: An Enabling Framework for Parallel Optimization on the Computational Grid. In: Fifth IEEE International Symposium on Cluster Computing and the Grid (CCGrid 2005), vol. 2, pp. 702–709 (2005)
Ramírez, M.A., Bernal, A., Castro, H., Walteros, J.L., Medaglia, A.L.: JG2A: A Grid-Enabled Object-Oriented Framework for Developing Genetic Algorithms. COPA (2009)
Liu, C., Zhao, Z., Liu, F.: An Insight into the Architecture of Condor - A Distributed Scheduler. In: CNMT International Symposium on Computer Network and Multimedia Technology (2010)
Voigt, H.-M., Born, J., Santibañez-Koref, I.: Modelling and Simulation of Distributed Evolutionary Search Processes for Function Optimization. In: Schwefel, H.-P., Männer, R. (eds.) PPSN 1990. LNCS, vol. 496, pp. 373–380. Springer, Heidelberg (1991)
Starkweather, T., Whitley, D., Mathias, K.: Optimization using Distributed Genetic Algorithms. In: Schwefel, H.-P., Männer, R. (eds.) PPSN 1990. LNCS, vol. 496, pp. 176–185. Springer, Heidelberg (1991)
Laszewski, G.v., Gawor, J., Lane, P., Rehn, N., Russell, M., Jackson, K.: Features of the Java Commodity Grid Kit. In: Concurrency and Computation: Practice and Experience, vol. 14, pp. 1045–1055. John Wiley & Sons, Ltd., Chichester (2002)
Sengoku, H., Yoshihara, I.: A Fast TSP Solution using Genetic Algorithm. In: Information Processing Society of Japan 46th Nat’l. Conv. (1993)
Larrañaga, P., Kuijpers, C.M.H., Murga, R.H., Inza, I., Dizdarevic, S.: Genetic Algorithms for the Travelling Salesman Problem: A Review of Representations and Operators. Artificial Intelligence Review 13, 129–170 (1999)
Reinelt, G.: TSPLIB - A Traveling Salesman Problem Library. ORSA Journal on Computing 3, 376–384 (1991)
Applegate, D., Bixby, R., Chvatal, V., Cook, W.: Finding Cuts in the TSP (A Preliminary Report). Research Report, Rice University (1994)
Author information
Authors and Affiliations
Editor information
Editors and Affiliations
Rights and permissions
Copyright information
© 2010 Springer-Verlag Berlin Heidelberg
About this paper
Cite this paper
Limmer, S., Fey, D. (2010). Framework for Distributed Evolutionary Algorithms in Computational Grids. In: Cai, Z., Hu, C., Kang, Z., Liu, Y. (eds) Advances in Computation and Intelligence. ISICA 2010. Lecture Notes in Computer Science, vol 6382. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-16493-4_18
Download citation
DOI: https://doi.org/10.1007/978-3-642-16493-4_18
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-642-16492-7
Online ISBN: 978-3-642-16493-4
eBook Packages: Computer ScienceComputer Science (R0)