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Evolutionary Computing within Grid Environment

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Book cover Advances in Evolutionary Computing for System Design

Part of the book series: Studies in Computational Intelligence ((SCI,volume 66))

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Evolutionary computing (EC) techniques such as genetic algorithms (GA), genetic programming (GP), evolutionary programming (EP) and evolution strategies (ES) mimic nature through natural selection to perform complex optimisation processes. Grid-enabled environment provides suitable framework for EC techniques due to its computational and data capabilities. In addition, the semantic and knowledge Grids aid in the design search and exploration for multi-objective optimisation tasks. This chapter explores some problem solving environments such as Geodise (Grid-Enabled Optimisation Design Search for Engineering), FIPER (Federated Intelligent Product Environment), SOCER (Service-Oriented Concurrent Environment), DAME (Distributed Aircraft Maintenance Environment) and Globus toolkit to demonstrate how EC techniques can be performed more efficiently within a Grid environment. Service-oriented and autonomic computing features of Grid are discussed to highlight how EC algorithms can be published as services by service providers and used by service requestors dynamically. Grid computational steering and visualisation are features that can be used for real-time tuning of parameters and visual display of optimal solutions. This chapter demonstrates that grid-enabled evolutionary computing marks the future of optimisation techniques.

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Authors and Affiliations

  1. Decision Engineering Centre, Manufacturing Department, School of Applied Sc, Cranfield University, Cranfield, MK43 0AL, Bedfordshire, UK

    Ashutosh Tiwari, Gokop Goteng & Rajkumar Roy

Authors
  1. Ashutosh Tiwari
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  2. Gokop Goteng
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  3. Rajkumar Roy
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Editor information

Editors and Affiliations

  1. University of South Australia, Adelaide, Mawson Lakes Campus, 5095, South Australia, Australia

    Lakhmi C. Jain

  2. Computing Laboratory, Wolfson Building Parks Road, OX1 3QD, Oxford, England

    Vasile Palade

  3. National University of Singapore, Block E4-06-08, 4 Engineering Drive 3, 117576, Singapore

    Dipti Srinivasan

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© 2007 Springer-Verlag Berlin Heidelberg

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Tiwari, A., Goteng, G., Roy, R. (2007). Evolutionary Computing within Grid Environment. In: Jain, L.C., Palade, V., Srinivasan, D. (eds) Advances in Evolutionary Computing for System Design. Studies in Computational Intelligence, vol 66. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-540-72377-6_10

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  • DOI: https://doi.org/10.1007/978-3-540-72377-6_10

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-540-72376-9

  • Online ISBN: 978-3-540-72377-6

  • eBook Packages: EngineeringEngineering (R0)

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