Экономические науки/ 8.Математические методы в экономике

Cand.ec.sc. Vlasyuk Y.A.
Tavria State Agrotechnological University, Ukraine
Enterprise Activities Simulation Modeling Problems and Advantages

Simulation modeling is the most powerful and versatile method for investigating and evaluating the effectiveness of systems the behavior of which depends on the impact of random factors. This method allows us to solve the problems of high complexity and provides a simulation of various processes with lots of levels and elements as well as a complex system of relationships between them. Therefore, simulation modeling is effectively used in systems analysis having complex structure in order to solve specific problems.

Constructing this type of models implies choosing the parameters the values of which are changeable and parameters the values of which having fixed. Then the experimental results are being processed. The modeling system enables not only to predict its behavior, but also to learn much more about the interactions of the system components than if monitoring the real system.

The peculiarity of the simulation is that the simulation model allows to reproduce the simulated objects keeping:

– maintaining its logic structure;

– maintaining its behavioral properties (time-sequence of events occurring in the system), namely dynamics of interactions [2].

Simulation modeling of economic processes usually used in two cases:

– to manage complex business process when simulation model of managed economic object is used as a means in an adaptive control system loop, created on the basis of information technologies;

– in experiments with discrete-continuous models of complex economic objects for tracking their dynamics in emergency situations involving risk, natural modeling of which is undesirable or impossible [1].

Simulation modeling is an important factor in decision support systems providing, as it allows to:

– explore a large number of alternatives (solutions);

– play different scenarios for any input.

The major advantage of simulation is that the researcher can to test new strategies and during the decision-making, can always get the answer to the question " What will happen if ?... ". Simulation model allows to forecast when it comes about projected system or making decisions the processes of development (in cases where the actual system does not yet exist). [2]

The simulation model enables to provide a variety of simulation processes detail level including the highest one.

Enterprises operating under weakly regulated market relations can also be considered as a complex system. For a focused study of the system structure and its functions it is expedient to apply simulation methods. Since, in most cases, experiments on real objects are unacceptable due to inability to precisely predict the behavior and impact of the environment on modeling object and the high cost of this experiment. In addition, these models are more flexible and are able to address the needs of a particular organization, department and even individual manager.

As noted by T. Naylor [3], the experience of creating business models in the United States shows that the development of mathematical models, even for systems entity of this scale as a company is a difficult research problem. Thus, not only the phase of the experiment, but its planning as well needs careful development. Since the model should be based on a solid empirical basis it is prerequisite to obtain reliable information, being particularly problematic for companies operating in highly competitive environment. Besides, there is the problem of choosing a method for gathering information providing needed volume and quality at the lowest cost.

Additional difficulties in the business model construction are associated with the need for certain understanding of the actual decision-making processes in organizations. As a consequence, the modeler must be competent in matters of decision-making theory, organization theory, psychology, sociology, politics, economics and production management.

Summarizing the above, we can come to the following conclusions:

– simulation is the most valuable in the core of a decision support systems, as it allows to explore a large number of alternatives and play different scenarios for any input;

– simulation models should be used in situations where the experiment on real objects is economically unjustified;

– simulation models allow to conduct research under conditions of uncertainty, with incomplete and inaccurate data;

– simulation provides multi-variance results;

– simulation allows not only to explore the parts of the system and their interaction, but also to make predictions;

– simulation models can use both static and dynamic description of the system.

Preferences:

1. Духанов, А. В. Имитационное моделирование сложных систем: курс лекций / А. В. Духанов, О.Н. Медведева; Владим. гос. ун-т. – Владимир: Изд-во Владим. гос. ун-та, – 2010, 115 с.

2. Информационный сайт IT Teach.ru, Сущность метода имитационного моделирования [Электронный ресурс]: – Электронные текстовые данные. – Режим доступа http://itteach.ru/statisticheskoe-modelirovanie/suschnost-metoda-imitatsionnogo-modelirovaniya.

3. Naylor, T. H. Computer Simulation Experiments with Models of Eco Nomic Systems / Thomas H. Naylor, James M. Boughton; John Wiley & Sons Australia, Limited, – 1971, 502 p.