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Simulated Annealing in Finding Optimum Groups of Learners of UML

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Intelligent Interactive Multimedia Systems and Services

Part of the book series: Smart Innovation, Systems and Technologies ((SIST,volume 6))

Abstract

The Simulated Annealing (SA) algorithm (Kirkpatrick et al. 1983) is a genetic algorithm that serves as a general optimization technique for solving combinatorial optimization problems. The local optimization algorithms start with an initial solution and repeatedly search for a better solution in the neighborhood with a lower cost. So, the locally optimal solution to which they result is this with the lower cost in the neighborhood.

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Authors and Affiliations

  1. Department of Informatics, University of Piraeus, 80 Karaoli & Dimitriou St., 18534, Piraeus, Greece

    Kalliopi Tourtoglou & Maria Virvou

Authors
  1. Kalliopi Tourtoglou
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  2. Maria Virvou
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Editor information

Editors and Affiliations

  1. Dept. of Informatics, University of Piraeus , 185 34, Piraeus, Greece

    George A. Tsihrintzis  & Maria Virvou  & 

  2. Dipto. Tecnologie dell’Informazione, Universita degli Studi di Milano , Via Bramante, 65, 26013, Crema, Italy

    Ernesto Damiani

  3. KES International , Shoreham-by-Sea, P.O. Box 2115, BN43 9AF, UK

    Robert J. Howlett

  4. School of Electrical and Information Engineering, University of South Australia , Mawson Lakes Campus, SA 5095, Adelaide, South Australia, Australia

    Lakhmi C. Jain

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Tourtoglou, K., Virvou, M. (2010). Simulated Annealing in Finding Optimum Groups of Learners of UML. In: Tsihrintzis, G.A., Damiani, E., Virvou, M., Howlett, R.J., Jain, L.C. (eds) Intelligent Interactive Multimedia Systems and Services. Smart Innovation, Systems and Technologies, vol 6. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-14619-0_15

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  • DOI: https://doi.org/10.1007/978-3-642-14619-0_15

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-642-14618-3

  • Online ISBN: 978-3-642-14619-0

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