Estimation Models Generation using Linear Genetic Programming

The use of decision rules and estimation techniques is increasingly common for decision making. In recent years studies were conducted which applies Genetic Programming (GP) to obtain rules to make predictions. A new branch in the area of Evolutionary Algorithms (EA) is Linear Genetic Programming (LGP). LGP evolves instructions sequences of an imperative programming language. This paper proposes estimation models generation for time series forecasting using LGP. The forecasting result for the Consumer Price Index (CPI) and the price of soybeans per ton shows the potential of this new proposal.