تخمين تابع تقاضاي بنزين در بخش حمل و نقل با استفاده از الگوريتم ژنيتك

Estimating Gasoline Demand Function in the Transportation Sector Using Genetic Algorithm

Consumption of light petroleum products, particularly gasoline, plays a fundametal role in economic growth and development of countries considering its impact on the transport sector. Evaluation of factors that influence the demand for gasoline is necessary for sound planning to reach desired economic objectives. In this paper we use the Genetic Algorithm Technique, to estimate gasoline demand in the transport sector for period (1353-85) in the form of linear, quadratic and exponential equations. The knowledge gained about gasoline demand is then used to forecast gasoline consumption in the transport sector until 1404 under different scenarios. In this paper gasoline consumption is considered to be a function of GDP, gasoline price, population, average age of the automobile fleet and consumption efficiency. The results indicate that the quadratic model has greater predictive power than other models for estimating gasoline demand.