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Assesing demand in stochastic locational planning problems: An Artificial Intelligence approach for emergency service systems

Author

Listed:
  • Photis, Yorgos N.
  • Grekoussis, George

Abstract

The efficiency of emergency service systems is measured in terms of their ability to deploy units and personnel in a timely and effective manner upon an event’s occurrence. Aiming to exploit stochastic demand, spatial tracing and location analysis of emergency incidents are examined through the utilisation of Artificial Intelligence in two interacting levels. Firstly, spatio-temporal point pattern of demand is analysed by a new genetic algorithm. The proposed genetic algorithm interrelates sequential events formulating moving events and as a result, every demand point pattern is correlated both to previous and following events. Secondly, the approach provides the ability to predict, by means of neural networks optimised by genetic algorithms, how the pattern of demand will evolve and thus location of supplying centres and/or vehicles can be optimally defined. Neural networks provide the basis for a spatio-temporal clustering of demand, definition of the relevant centres, formulation of possible future states of the system and finally, definition of locational strategies for the improvement of the provided services.

Suggested Citation

  • Photis, Yorgos N. & Grekoussis, George, 2003. "Assesing demand in stochastic locational planning problems: An Artificial Intelligence approach for emergency service systems," MPRA Paper 20678, University Library of Munich, Germany.
    • Handle: RePEc:pra:mprapa:20678
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    File URL: https://mpra.ub.uni-muenchen.de/20678/1/MPRA_paper_20678.pdf
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    References listed on IDEAS

    as
    1. Jossef Perl & Peng-Kuan Ho, 1990. "Public Facilities Location under Elastic Demand," Transportation Science, INFORMS, vol. 24(2), pages 117-136, May.
    2. Owen, Susan Hesse & Daskin, Mark S., 1998. "Strategic facility location: A review," European Journal of Operational Research, Elsevier, vol. 111(3), pages 423-447, December.
    Full references (including those not matched with items on IDEAS)

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    More about this item

    Keywords

    Locational planning; Point Pattern Analysis; Spatial analysis; Artificial Intelligence;
    All these keywords.

    JEL classification:

    • R53 - Urban, Rural, Regional, Real Estate, and Transportation Economics - - Regional Government Analysis - - - Public Facility Location Analysis; Public Investment and Capital Stock
    • C45 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods: Special Topics - - - Neural Networks and Related Topics
    • C61 - Mathematical and Quantitative Methods - - Mathematical Methods; Programming Models; Mathematical and Simulation Modeling - - - Optimization Techniques; Programming Models; Dynamic Analysis

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