Abstract

This paper applies genetic algorithms to tourism forecasting. To date, genetic algorithms have normally been used as an optimization method. Their application to forecasting with real-world data has not been studied extensively. The paper illustrates how genetic algorithms can be used for this purpose and the new kind of forecast that is obtained. Specifically, the algorithms are applied to a real tourist population, and the characteristics and decisions of each future tourist are forecast. The results suggest that tourism forecasting based on genetic algorithms could reduce the risk of decision making in tourism planning.

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