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A Comparative Analysis of the Performance of Evolutionary Algorithms and Logit Models in Spatial Networks

In: Spatial Economic Science

Author

Listed:
  • Aura Reggiani

    (University of Bologna)

  • Peter Nijkamp

    (Free University)

  • Enrico Sabella

    (University of Bologna)

Abstract

The analysis of complex networks has in recent years become an important research issue in spatial economics and regional science. An important methodological step forward in this context has been offered by synergetic theory and the relative dynamics concept of network evolution (see, for a review, Nijkamp and Reggiani 1998). These concepts have intensified the search for universal principles driving non-linear dynamic systems with a particular interest in methodological underpinnings and instruments. In modern research in this field a new class of models, based on bio-computing and artificial intelligence, has recently come to the fore. These new approaches demonstrated a high potential in modelling high-dimensional spatial networks.

Suggested Citation

  • Aura Reggiani & Peter Nijkamp & Enrico Sabella, 2000. "A Comparative Analysis of the Performance of Evolutionary Algorithms and Logit Models in Spatial Networks," Advances in Spatial Science, in: Aura Reggiani (ed.), Spatial Economic Science, chapter 16, pages 331-354, Springer.
    • Handle: RePEc:spr:adspcp:978-3-642-59787-9_16
    DOI: 10.1007/978-3-642-59787-9_16
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    Cited by:

    1. Aura Reggiani & Thomas de Graaff & Peter Nijkamp, 2001. "Resilience: An Evolutionary Approach to Spatial Economic Systems," Tinbergen Institute Discussion Papers 01-100/3, Tinbergen Institute.

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