Genetic algorithms in forecasting of Internet shops demand

Chodak, Grzegorz (2009): Genetic algorithms in forecasting of Internet shops demand. Published in: Information systems architecture and technology : system analysis in decision aided problems (2009): pp. 59-68.

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.

• Item Type: MPRA Paper
• Language: English
• Keywords: abc analysis, inventory control, internet shop,e-commerce
• Subjects: D - Microeconomics > D8 - Information, Knowledge, and Uncertainty > D81 - Criteria for Decision-Making under Risk and Uncertainty; C - Mathematical and Quantitative Methods > C6 - Mathematical Methods ; Programming Models ; Mathematical and Simulation Modeling > C61 - Optimization Techniques ; Programming Models ; Dynamic Analysis; C - Mathematical and Quantitative Methods > C8 - Data Collection and Data Estimation Methodology ; Computer Programs > C81 - Methodology for Collecting, Estimating, and Organizing Microeconomic Data ; Data Access

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