Simulation and systems analysis in Agriculture

The appearance of simulation methods in agriculture has grown in parallel with the spread of systems analysis and with an increasing demand for a more exact understanding of the real world. New vistas are opened up by simulation methods with their greater elasticity in agrarian economic research, and their provision of a better foundation for agricultural decisions at various levels. That production processes of agriculture are dynamic in nature, influenced by random effects, and based upon biological principles, means that they are suitable for the study of agricultural problems using a systems approach based on simulation. It is thus no coincidence that agricultural specialists have recently shown growing interest in this method.

Systems approach and simulation methods are now used in almost every field of science. The word simulation itself can be used in various, more or less synonymous ways. In brief, simulation is an experiment to bring about relations in conditions approaching those of the real world, and to explore the probability of the predicted behaviour of the experimented phenomenon under real conditions. The essence of systems simulation implies the reconstruction of a certain part of reality, or the modelling of systems existing in reality, and the execution of an experiment on the basis of this model in order to obtain a fuller understanding of a phenomenon or a problem.

Experiments can rarely be carried out in economic life, and so simulation was not considered for a long while in this field. But as mathematics and computer techniques developed, they created the possibility of more extensive experimentation in the economic sphere. Such experimentation might be based on a mathematical model describing the phenomenon in question. In the economic sciences, including agricultural economics, the essence of simulation is to study economic processes with the aid of mathematical models.

Simulation methods, even in economics, are essentially more colourful than mathematical programming or other analytical methods. The application of these methods is predominantly problem-oriented and closely related to systems approach. It is often said that in reality the application of simulation is always specific to a situation, as the problems studied are never exactly the same. But it would be an exaggeration to imply that systems simulation does not possess elements and rules which can be generally applied. It is true that simulation, by virtue of its rules, does not have such formal procedures as methods of mathematical analysis. Simulation does not represent an individual, specific type of model but is rather the application of a special procedure of solution; of a method of exploration of problems; or a type of approach. But the logic of simulating economic problems is the same in each case. Certain methodological rules can be applied more widely, coupled with the demands originating from the peculiarities of concrete problems.