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Linkage in Evolutionary Computation pp 159–187Cite as

Parallel GEAs with Linkage Analysis over Grid

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Part of the book series: Studies in Computational Intelligence ((SCI,volume 157))

Summary

This chapter describes the latest trends in the field of parallel/distributed computing and the effect of these trends over Genetic and Evolutionary Algorithms (GEAs) especially linkage based GEAs. We concentrate mainly on the Grid computing paradigm which is widely accepted as the most distributed form of computing; due to the advent of Service Oriented Architecture (SOA) and other technologies, Grid has gained a lot of attention in the recent years. We also present a framework that can help users in implementation of metaheuristics based optimization algorithms (including GEAs) over a Grid computing environment. We call this framework MetaHeuristics Grid (MHGrid). Moreover, we give a theoretical analysis of the maximum speed-up achievable by using MHGrid. We also discuss our experience of working with Grids.

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References

  1. Wickramasinghe, W., Steen, M.V., Eiben, A.: Peer-to-peer evolutionary algorithms with adaptive autonomous selection. In: GECCO 2007: Proceedings of the 9th annual conference on Genetic and evolutionary computation, pp. 1460–1467. ACM, New York (2007)

    Chapter  Google Scholar 

  2. http://www.top500.org (June 2007)

  3. Foster, I., Kesselman, C.: The Grid: Blueprint for a New Computing Infrastructure. Morgan-Kaufman, San Francisco (1999)

    Google Scholar 

  4. Fox, G., Aktas, M.S., Aydin, G., Gadgil, H., Pallickara, S., Pierce, E., Sayar, A.: Algorithms and the Grid. Computing and Visualization in Science (CVS) (2005)

    Google Scholar 

  5. Fox, G.: Grids of Grids of Simple Services. Computing in Science and Engg. 6(4), 84–87 (2004)

    Article  Google Scholar 

  6. Booth, D., Haas, H., McCabe, F., Newcomer, E., Champion, M., Ferris, C., Orchard, D.: Web Service Architecture. In: W3C Working Group Note W3C (2004)

    Google Scholar 

  7. Foster, I., Kishimoto, H., Savva, A., Berry, D., Djaoui, A., Grimshaw, A., Horn, B., Maciel, F., Siebenlist, F., Subramaniam, R., Treadwell, J., Reich, J.V.: The Open Grid Services Architecture, Version 1.0. GGF informational document Global Grid Forum(GGF) (2005)

    Google Scholar 

  8. Christensen, E., Curbera, F., Meredith, G., Weerawarana, S.: Web Services Description Language (WSDL) 1.1. W3C Working Group Note W3C (2001)

    Google Scholar 

  9. Mitra, N., Lafon, Y.: SOAP Version 1.2 Part 0: Primer, 2nd edn. W3C Working Group Note W3C (2007)

    Google Scholar 

  10. Foster, I.: Globus Toolkit Version 4: Software for Service-Oriented Systems. In: Jin, H., Reed, D., Jiang, W. (eds.) NPC 2005. LNCS, vol. 3779, pp. 2–13. Springer, Heidelberg (2005)

    Chapter  Google Scholar 

  11. Miura, K.: Overview of Japanese science Grid project: NAREGI. Technical Report 3 (2006)

    Google Scholar 

  12. Foster, I.: What is the Grid? - a three point checklist. GRIDtoday 1(6) (2002)

    Google Scholar 

  13. Lim, D., Ong, Y.-S., Jin, Y., Sendhoff, B., Lee, B.-S.: Efficient Hierarchical Parallel Genetic Algorithms using Grid computing. Future Gener. Comput. Syst. 23(4), 658–670 (2007)

    Article  Google Scholar 

  14. Amdahl, G., Gene, M.: Validity of the single processor approach to achieving large scale computing capabilities. pp. 79–81 (2000)

    Google Scholar 

  15. Gustafson, L.: Reevaluating Amdahl’s law. Commun. ACM 31(5), 532–533 (1988)

    Article  Google Scholar 

  16. Cantú-Paz, E.: A summary of research on parallel genetic algorithms. Technical report IlliGAL 95007, University of Illinois at Urbana-Champaign (1995)

    Google Scholar 

  17. Alba, E., Troya, J.: A survey of parallel distributed genetic algorithms. Complex. 4(4), 31–52 (1999)

    Article  MathSciNet  Google Scholar 

  18. Gordon, V., Whitley, D.: Serial and Parallel Genetic Algorithms as Function Optimizers. In: Forrest, S. (ed.) Proceedings of the Fifth International Conference on Genetic Algorithms, pp. 177–183. Morgan Kaufmann, San Mateo (1993)

    Google Scholar 

  19. Tanese, R.: Distributed Genetic Algorithms. In: Proceedings of the 3rd International Conference on Genetic Algorithms, pp. 434–439. Morgan Kaufmann Publishers Inc., San Francisco (1989)

    Google Scholar 

  20. Whitley, D., Starkweather, T.: GENITOR II: a distributed genetic algorithm. J. Exp. Theor. Artif. Intell. 2(3), 189–214 (1990)

    Article  Google Scholar 

  21. Davidor, Y.: A Naturally Occurring Niche and Species Phenomenon: The Model and First Results. In: Proceedings of the 4th International Conference on Genetic Algorithms(ICGA), pp. 257–263. Morgan Kaufmann, San Diego (1991)

    Google Scholar 

  22. Gorges-Schleuter, M.: ASPARAGOS An Asynchronous Parallel Genetic Optimization Strategy. In: Proceedings of the 3rd International Conference on Genetic Algorithms, pp. 422–427. Morgan Kaufmann Publishers Inc., San Francisco (1989)

    Google Scholar 

  23. Manderick, B., Spiessens, P.: Fine-grained parallel genetic algorithms. In: Proceedings of the third international conference on Genetic algorithms, pp. 428–433. Morgan Kaufmann Publishers Inc., San Francisco (1989)

    Google Scholar 

  24. De Jong, K., Sarma, J.: On Decentralizing Selection Algorithms. In: Eshelman, L. (ed.) Proceedings of the Sixth International Conference on Genetic Algorithms, pp. 17–23. Morgan Kaufmann, San Francisco (1995)

    Google Scholar 

  25. Gorges-Schleuter, M.: A Comparative Study of Global and Local Selection in Evolution Strategies. In: Eiben, A.E., Bäck, T., Schoenauer, M., Schwefel, H.-P. (eds.) PPSN 1998. LNCS, vol. 1498, p. 367. Springer, Heidelberg (1998)

    Chapter  Google Scholar 

  26. Eiben, A., Schoenauer, M., van Krevelen, D., Hobbelman, M., ten Hagen, M., van het Schip, R.: Autonomous selection in evolutionary algorithms. In: GECCO 2007: Proceedings of the 9th annual conference on Genetic and evolutionary computation, p. 1506. ACM, New York (2007)

    Chapter  Google Scholar 

  27. Cantú-Paz, E., Goldberg, D.: Parallel Genetic Algorithms with Distributed Panmictic Populations. Technical report IlliGAL 99006, University of Illinois at Urbana-Champaign (1999)

    Google Scholar 

  28. Cantú-Paz, E.: A Survey of Parallel Genetic Algorithms. Technical report IlliGAL 97003, University of Illinois at Urbana-Champaign (1997)

    Google Scholar 

  29. Imade, H., Morishita, R., Ono, I., Ono, N., Okamoto, M.: A grid-oriented genetic algorithm for estimating genetic networks by S-systems. In: SICE 2003 Annual Conference, vol. 3(4-6), pp. 2750–2755 (2003)

    Google Scholar 

  30. Imade, H., Morishita, R., Ono, I., Ono, N., Okamoto, M.: A grid-oriented genetic algorithm framework for bioinformatics. New Gen. Comput. 22(2), 177–186 (2004)

    Article  MATH  Google Scholar 

  31. Herrera, J., Huedo, E., Montero, R., Llorente, I.: A Grid-Oriented Genetic Algorithm. In: Sloot, P.M.A., Hoekstra, A.G., Priol, T., Reinefeld, A., Bubak, M. (eds.) EGC 2005. LNCS, vol. 3470, pp. 315–322. Springer, Heidelberg (2005)

    Google Scholar 

  32. Deerman, K.: Protein Structure Prediction Using Parallel Linkage Investigating Genetic Algorithms. Master’s thesis Air force Inst of Tech, Wright-Patterson AFB OH School of Engineering (1999)

    Google Scholar 

  33. Munetomo, M., Murao, N., Akama, K.: A Parallel Genetic Algorithm Based on Linkage Identification. In: Cantú-Paz, E., Foster, J.A., Deb, K., Davis, L., Roy, R., O’Reilly, U.-M., Beyer, H.-G., Kendall, G., Wilson, S.W., Harman, M., Wegener, J., Dasgupta, D., Potter, M.A., Schultz, A., Dowsland, K.A., Jonoska, N., Miller, J., Standish, R.K. (eds.) GECCO 2003. LNCS, vol. 2724. Springer, Heidelberg (2003)

    Google Scholar 

  34. Munetomo, M., Goldberg, D.: Identifying Linkage Groups by Nonlinearity/Non-monotonicity Detection. In: Proceedings of the Genetic and Evolutionary Computation Conference, Orlando, Florida, USA, 13-17 1999, vol. 1, pp. 433–440. Morgan Kaufmann, San Francisco (1999)

    Google Scholar 

  35. Munetomo, M.: Linkage Identification Based on Epistasis Measures to Realize Efficient Genetic Algorithms. In: Proceedings of the 2002 Congress on Evolutionary Computation, pp. 1332–1337 (2002)

    Google Scholar 

  36. Karpowicz, M., Niewiadomska-Szynkiewicz, E., Zientak, M.: A Modified Parallel Genetic Algorithm Based on Linkage Identification. In: KAEiOG, Kazimierz Dolny (2004)

    Google Scholar 

  37. Pelikan, M., Goldberg, D., Cantú-Paz, E.: Linkage Problem, Distribution Estimation, and Bayesian Networks. Technical Report 98013 Urbana, IL (1998)

    Google Scholar 

  38. Ocenásek, J., Schwarz, J.: The Parallel Bayesian Optimization Algorithm. In: Proceedings of the European Symposium on Computational Inteligence, pp. 61–67. Springer, Heidelberg (2000)

    Google Scholar 

  39. Wolpert, H.D., Macready, G.W.: No Free Lunch Theorems for Search. Technical Report SFI-TR-95-02-010 Santa Fe, NM (1995)

    Google Scholar 

  40. Takemiya, H., Tanaka, Y., Sekiguchi, S., Ogata, S., Kalia, R., Nakano, A., Vashishta, P.: Sustainable adaptive grid supercomputing: multiscale simulation of semiconductor processing across the pacific. In: Löwe, W., Südholt, M. (eds.) SC 2006, p. 106. ACM, New York (2006)

    Chapter  Google Scholar 

  41. Czyzyk, J., Mesnier, M., More, J.: The NEOS Server. IEEE Journal on Computational Science and Engineering 5, 68–75 (1998)

    Article  Google Scholar 

  42. Gropp, W., Mor’e, J.: Optimization environments and the NEOS server (1997)

    Google Scholar 

  43. Dolan, E.: The NEOS Server 4.0 Administrative Guide. Technical Memorandum ANL/MCS-TM-250 Mathematics and Computer Science Division, Argonne National Laboratory (2001)

    Google Scholar 

  44. Cox, S., Chen, L., Campobasso, S., Duta, M., Eres, M., Giles, M., Goble, C., Jiao, Z., Keane, A., Pound, G., Roberts, A., Shadbolt, N., Tao, F., Wason, J., Xu, F.: Grid Enabled Optimisation and Design Search (GEODISE). Technical report (2002)

    Google Scholar 

  45. Abramson, D., Lewis, A., Peachy, T.: Nimrod/O: A Tool for Automatic Design Optimization. In: The 4th International Conference on Algorithms & Architectures for Parallel Processing (ICA3PP 2000), Hong Kong (2000)

    Google Scholar 

  46. Novotny, J., Russell, M., Wehrens, O.: GridSphere: a portal framework for building collaborations: Research Articles. Concurr. Comput.: Pract. Exper. 16(5), 503–513 (2004)

    Article  Google Scholar 

  47. Symour, K., Nakada, H., Matsuoka, S., Dongarra, J., Lee, C., Casanova, H.: Overview of GridRPC: A remote procedure call API for grid computing. In: Proc. 3rd Int. Workshop Grid Computing, pp. 274–278 (2002)

    Google Scholar 

  48. Tanaka, Y., Nakada, H., Sekiguchi, S., Suzumura, T., Matsuoka, S.: Ninf-G: A Reference Implementation of RPC-based Programming Middleware for Grid Computing. Journal of Grid Computing 1(1), 41–51 (2003)

    Article  Google Scholar 

  49. Frey, J., Tannenbaum, T., Foster, I., Livny, M., Tuecke, S.: Condor-G: A Computation Management Agent for Multi-Institutional Grids. In: Proceedings of the Tenth IEEE Symposium on High Performance Distributed Computing (HPDC), San Francisco, California, pp. 7–9 (2001)

    Google Scholar 

  50. Ishikawa, Y., Kaneo, Y., Edamoto, M., Okazaki, F., Koie, H., Takano, R., Kudoh, T., Kodama, Y.: Overview of the GridMPI Version 1.0. In: SWoPP 2005 (2005)

    Google Scholar 

  51. Munawar, A., Wahib, M., Munetomo, M., Akama, K.: Standardization of Interfaces for Meta-Heuristics based Problem Solving Framework over Grid Environment. In: Proccedings of HPCAsia 2007, Seoul, South Korea (2007)

    Google Scholar 

  52. Alba, E., Garc-Nieto, J., Nebro, A.: On the Configuration of Optimization Algorithms by Using XML Files (2003)

    Google Scholar 

  53. Munawar, A., Wahib, M., Munetomo, M., Akama, K.: Optimization Problem Solving Framework Employing GAs with Linkage Identification over a Grid Environment. In: CEC 2007: Proceedings of IEEE congress on Evolutionary Computation, Singapore (2007)

    Google Scholar 

  54. Wahib, M., Munawar, A., Munetomo, M., Akama, K.: A General Service-Oriented Grid Computing Framework For Global Optimization Problem Solving. In: SCC 2008: Proceedings of the 2008 IEEE International Conference on Services Computing, Honolulu, Hawaii, USA. IEEE, Los Alamitos (to appear, 2008)

    Google Scholar 

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Authors and Affiliations

  1. Graduate School of Information Science & Technology, Hokkaido University, Japan

    Asim Munawar & Mohamed Wahib

  2. Information Initiative Center, Hokkaido University, Japan

    Masaharu Munetomo & Kiyoshi Akama

Authors
  1. Asim Munawar
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  2. Mohamed Wahib
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  3. Masaharu Munetomo
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  4. Kiyoshi Akama
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Ying-ping Chen Meng-Hiot Lim

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Munawar, A., Wahib, M., Munetomo, M., Akama, K. (2008). Parallel GEAs with Linkage Analysis over Grid. In: Chen, Yp., Lim, MH. (eds) Linkage in Evolutionary Computation. Studies in Computational Intelligence, vol 157. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-540-85068-7_8

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  • DOI: https://doi.org/10.1007/978-3-540-85068-7_8

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  • Print ISBN: 978-3-540-85067-0

  • Online ISBN: 978-3-540-85068-7

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