A Novel Fuzzy Evolutionary Algorithm for Forecasting of International Trade in Dynamical Environment

We describe in this paper non-linear mathematical models that can be used to study the dynamics of international trade. Mathematical models of International Trade (IT), between three or more countries, can show very complicated dynamics in time (with the possible occurrence of chaotic behavior). The simulation of these models is critical in understanding the behavior of the relevant financial and economical variables for the problem of IT. Also, performing the simulations for different parameter values of the models will enable the forecasting of future IT. The problem of forecasting of IT has been solved in this paper buy using evolutionary algorithm combining fuzzy logic techniques. The importance of forecasting of IT can be measured if we consider that one of the goals for a specific country is to find the optimum benefit from its international trade with other countries.