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Heuristic Techniques in Optimisation

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Guide to Computational Modelling for Decision Processes

Part of the book series: Simulation Foundations, Methods and Applications ((SFMA))

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Abstract

These approaches can be useful when the problem to be solved is large and/or complex, when a timely good solution is considered to be better than a late optimal solution.

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References

  1. Holland JH (1992) Adaption in natural and artificial systems. MIT Press, Cambridge

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  2. Goldberg D (1989) Genetic algorithms in search optimisation and machine learning. Addison Wesley, MA

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  3. Mitchell M (1998) An introduction to genetic algorithms. MIT Press, Cambridge

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  4. Glover F (1989) Tabu search—Part I. ORSA J Comput 1(3):190–206

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  5. Glover F (1990) Tabu search—part II. ORSA J Comput 2:4–32

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Correspondence to Stuart Berry .

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Lowndes, V., Berry, S. (2017). Heuristic Techniques in Optimisation. In: Berry, S., Lowndes, V., Trovati, M. (eds) Guide to Computational Modelling for Decision Processes. Simulation Foundations, Methods and Applications. Springer, Cham. https://doi.org/10.1007/978-3-319-55417-4_4

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  • DOI: https://doi.org/10.1007/978-3-319-55417-4_4

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  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-319-55416-7

  • Online ISBN: 978-3-319-55417-4

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