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Genetic algorithms in forecasting of Internet shops demand

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Author Info

  • Chodak, Grzegorz

Abstract

The general aim of this article is to present genetic algorithms as a tool, that can be used in de-mand forecasting in internet shops. First part of article identities factors, which have to be taken into consideration during analysing demand in internet shops, e.g. dispersion of demand, delivery time in-fluence and different e-marketing factors. Specific form of used demand function is shown in the next section of the article. Then genetic algorithm is defined by its genetic operators acting on bit strings (examples of the operators are: crossover, inversion, and mutation) and its method of credit allocation (fitness evaluation and selection). Next the method of identification of the function parameters using genetic algorithms is shown. The next part of article shows appliance of presented genetic algorithm. The advantages and disadvantages of proposed method are shortly discussed in summary.

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File URL: http://mpra.ub.uni-muenchen.de/34034/
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Bibliographic Info

Paper provided by University Library of Munich, Germany in its series MPRA Paper with number 34034.

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Date of creation: 2009
Date of revision: 2009
Handle: RePEc:pra:mprapa:34034

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Related research

Keywords: abc analysis; inventory control; internet shop; e-commerce;

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  1. Chodak, Grzegorz & Kwaśnicki, Witold, 2000. "Genetic algorithms in seasonal demand forecasting," MPRA Paper 34099, University Library of Munich, Germany.
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Cited by:
  1. Chodak, Grzegorz & Latus, Łukasz, 2011. "Metody prognozowania popytu i zarządzanie gospodarką magazynową w polskich sklepach internetowych – wyniki badań
    [Methods of Demand Forecasting and Inventory Management in Polish Internet Sho
    ," MPRA Paper 36713, University Library of Munich, Germany.

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