The Methods of Non-optimum Analysis and the Application of Economic Reform

International Journal of Emerging Technology and Advanced Engineering

165

The Methods of Non-optimum Analysis and the

Application of Economic Reform

Ping He

Department of Information, Liaoning Police College, Dalian, 116036 China

[email protected]

Abstract—This paper presents a novel approach to non-optimum analysis based on experience recognition. Our goal is to provide support for optimization of uncertainty system. Our approach allows the practice courses and results of mankind are classified by their natures into two categories: optimum, and optimum. It is considered that the non-optimum system does not exclude the targets and the results of optimum in practice. The formation of non-optimum system serves as the basis for existence of optimum system in uncertainty. Besides, the various characteristics and functions of the optimum system can be measured from the non-optimum system. At the same time, it also puts forward the optimum measurement of the system along with non-optimum tracing and self-learning of the experience systems.

Keywords—Non-optimum category; man’s recognition, new methodology; experience learning; actual significances

I. INTRODUCTION

System non-optimum analysis is one of the youngest branches of information science; it is not ten year s old. The date of its birth can, In the following years, the research of systems’ non-optimum has developed very fast, both in theory and in practice, which involves non-optimum recognition of systems, evaluation of the optimum and non-optimum solutions, the non-non-optimum measurement of systems, the non-optimum differentiation and instruction of systems in the engineering areas.

The non-optimum analysis theory of systems, based on the results of the recognition and practice of mankind, establishes the most optimal and non-optimal research fields, in order to satisfy the subjective requirements of people and fulfill the objective regulations. The optimum category consists of the most optimum and optimum, which refers to the processes and results of success. The non-optimum category is composed of the processes and results of failures and acceptable, imperfect situations. Unfeasibility and unreasonableness are typical non-optimum. Although being feasible and reasonable in a certain degree, they still belong to the non-optimum category. In reality, every system belongs to the non-optimum category.

It meets the recognition and realization of mankind to analyze the causes of non-optimum system and the ways to reach optimum from the viewpoint of non-optimum category. This way of thinking is abbreviated as non-optimum tracing theory, and the theory of researching and tracing non-optimum is called non-optimum analysis theory of system. The paper probes into several problems of non-optimum systems from the viewpoint of information theory.

II. THE NON-OPTIMUM FOR MAN’S RECOGNITION

The concept of non-optimum is quite comprehensive. From the viewpoint of systems’ entity, non-optimum means unfeasible and unreasonable; from the viewpoint of systems’ behavior, it means non-ideal and non-good; from the viewpoint of systems’ capacity, it means ineffective and abnormal; from the viewpoint of systems’ change, it means obstacles, disturbance and influence. There exists a serious of non-optimum problem from the entity of the system to the change of the system, which causes non-optimum category. As to every kind of system engineering problems, there is the individual non-optimum category as well as the common non-optimum category. The so-called individual non-optimum category is decided by the characters of the system, while the common non-optimum category is an objective entity. Every system exists in a non-optimum category. Due to the needs of the system, certain conducts and functions of the system come into being, which are confirmed by the non-optimum category?

International Journal of Emerging Technology and Advanced Engineering

166 "General defeated" of 《The Art of War by Sun Bin》, the writers summed up the experiences of war, particularly the lessons of failures before the Spring and Autumn times and the Warring States. These historical literatures illustrated that ever since the ancient times, man has not only analyzed problems in the fields of optimum, but also in the fields of non-optimum. Thus the idea of non-optimum analysis has a significant position in the history of man’s recognition[2].

Man's knowledge of the objective world and of himself is always in the midst of ever deepening course. In human history, there has been many a social practice that was carried out partly or even wholly with blindness, thus making it impossible to avoid failures completely. Yet, each of the failures adds to the improvement of human understanding of the objective and subjective world. So those social efforts that have failed occupy important positions in the chronicle of human knowledge. The motto "failure is the mother of success" and‖ the virtues of failure" (Ref. [9], Research Corporation Newsletter, Winter, 2005) tells that human race learns from setbacks. But it fails in theorization and quantitative analysis.

III. METHODOLOGIES

In the science research, there lies always two schools of thinking differences in nature: one is the regular thinking, which goes along with the existed thinking pattern; the other is the reversed thinking, which goes against the existed thinking pattern. The history of scientific research shows that the regular thinking pattern might easily cause people to be rigid and stubborn, which lead to failures of scientific research; while the reversed thinking can enlighten scientists and lead to success of scientific research. The non-optimum analysis of systems is created by the reversed way of thinking. The research of non-optimum problem on systems and the tracing of non-optimum modes are interrelated and inter-perforated, and stand reciprocally contradictory. The former expresses the escape from non-optimum category and the latter displays the exploration of the most optimal mode and its procedure. Based on the interrelationship of the two research areas ( He Ping, 2004), the formation of non-optimum category and the constraint of non-optimum are the foundation to establish the optimum category. It means that only when man does the research out of the non-optimum category, can they be on their way to trace the most optimal modes.

System Engineering, a synthetic product of sophisticated science & technology, came into being in the 1950's. It abstracts a system into a model and searches for the most optical solution systematically under restrictions.

Due to the complexity of mankind’s practice, there are numbers of unknown and uncertain factors, longitudinal and transverse relationship of things, people’s behavior. Especially as the system heads to the orderly dynamic condition, some of the hidden troubles are not exposed, the achieved most optical modes are in unstable states. This implies that recognition and practice of mankind is featured by the exploration and pursuit not only in an optical category, but also, under many conditions, in a non-optical category.

That is to say when people are faced with urgent problems, they need not only to find out the most optical mode or realize the most optical aim, but also, more importantly, to get rid of the vicious influences of optimum accidents effectively as well as control the non-optimum factors of the system.

To decide whether a system is an optimal system is the key to analyze it. The aim of analyzing and researching systems of different realms is to find out the best goals and results of the system. However, it is not always that easy. The previous system analysts committed that it is impossible to realize optimum under a limited condition of time and resources. At the same time, behind the optimum, there is definitely a series of hypotheses, middle-way decisions, and predigestion of data. Under most conditions, the hypotheses of optimum do not exist. Although people have generalized this method to many fields, the results obtained can be only temporary, and sometimes cannot achieve the final goals.

Ever since nearly half a century, the optimum theory has undoubtedly contributed extensively every branch of science and technology. It is because of its wide use that people find out it is far from actual requirements. People wonder whether ideal model analysis can solve real problems. Furthermore, it is very hard to build up a mathematic model for many of the actual complicated problems. Especially when the system is uncertain, man can only limply build up the model, but can hardly get its solution. Although there are a lot of approximate methods and theories of solving, they are far from satisfaction.

International Journal of Emerging Technology and Advanced Engineering

167 IV. NON-OPTIMUM AND EXPERIENCE LEARNING

System experience provides the recognition of the non-optimum. When the experiences are different, the recognition of the non-optimums is different as well. In an artificial system, different people have different behaviors and stories, thus different experiences. The recognition of the non-optimum is selected and decided by the experience, and the reasonability of the experience’s selection is also a meaningful question for discussion. For example, the increase of the function of the system can reduce the non-optimum category, and the changes of the system’s behavior can cause new non-optimum factors, which change with the system’s behavior. Thus the non-optimum category of the actual system is composed of non-optimum syndrome, the amount of non-optimum changes and the potential non-optimum factors.

Under the prerequisites of the formation of the system’s experience, there is a process of recognition to the non-optimum system, which is a self-learning process. Natural non-optimum is a objective entity, which does not change with people’s will. However, when people get hold of the basic characteristics of the non-optimum, they can set up certain functions to avoid the non-optimum, which is not the main subject of the non-optimum analysis theory of the system. From the creation to the death of the system, there is an overall running procedure. In fact, a whole, standard running condition does not exist, and also breaches the development regulation of things. From the viewpoint of the dialectic from recognition to entity, this also accords with the entity and recognition to the non-optimum. For example, as a decision-maker of a concern, one first needs to do a series of work related to the management of the concern and the strategic development objectives. That is to say, to find out what methods to take, what problems to solve and what difficulties to conquer. The key to finish this series of work is to correctly find out the non-optimum problem that exists meanwhile with the objectives.

There are two situations in analyzing the experiences of non-optimum system: the inherent non-optimum syndrome under stable conditions of a system is decided by the function of the system; the non-optimum syndrome under unstable situations of the system is obtained through statistic analysis. That is to say, during the process of a systems development, non-optimum factors effect on the system, which causes a relationship that does not exist when the system is stable, and it is called optimum-born relationship. Every system has to have a non-optimum-born relationship; otherwise, the system goes into chaos when it is unstable.

For instance, in a strategic decision-making of a large chemical industry corporation, how to build up a non-optimum-born relationship is the key of the corporation’s survival and development. It works as this: through the yearlong experience of the corporation, a stable experience area is formed (according to certain experience-decision effect of each year), through which the reasons of unstable factors of the system can be reflected and non-optimum genes found. Of course, there are non-optimum genes everywhere in the system and what we need are the major genes, which are the major factors that cause the system to fluctuate to a certain extent. In the actual analysis of the system, some factors have direct relationship with the non-optimum genes, some indirect. More relative factors are more influenced by non-optimum genes. Therefore, the factors can be divided into the major non-optimum effect and the minor non-optimum effect. Minor non-optimum effect is influenced by other factors. The core of the tracing to the optimum influences starts from building up non-optimum syndrome and non-non-optimum cause of formation. The syndrome cannot really become the influence, and the actual non-optimum indeed influences the system, both of which come from non-optimum syndrome. There is a procedure of diagnosis from the syndrome to the cause of formation.

The diagnosis happens when the behavior of the system finishes, and includes: the cause of foundation of non-optimum from the major syndrome; the cause of foundation of non-optimum from the minor syndrome, which is the overall framework of the tracing to non-optimum.

V. ACTUAL APPLICATIONS

The development of human society is forever in the dynamic and uncertainty process of moving from the less ordered toward the more ordered larger system, which is toward its destination point cycle. However we must be aware of the hidden danger under the vigorous stream which may bring about slipped up in decision making and failures. Meanwhile we have already suffered a few slip up in decision making and failures in some areas to some extent. What’s more failures are that some failures suffered have been repeated and what could have been avoided has not.

International Journal of Emerging Technology and Advanced Engineering

168 Even if some model is considered optimum under the present circumstances, it is hard to be a stable one because it is in the midst of a dynamic process with quite a few hidden threats lurching and many horizontal or vertical sub-optimum states. So, if we try to set goals for the economic reform, make plans and take measures and advocate some optimum models simply following the optimum thinking methods out of blind subjective wish, well be actually putting the economic reform on an unreliable and unrealistic basis.

So we say that the non-optimum thinking and the methods of non-optimum analysis on systems with failure-avoiding as its basic aim are based on the non-optimum facts with its special ways of thinking, information gathering, analyzing and processing, and with the setting up of non-optimum system, these methods seek to lessen slipped up in decision making and failures, thus providing a new way of scientifically summarizing past lesson and making them lamppost for the future. There is profound potential for putting the non-optimum thinking into use in Chinas economic reform, and in other country’s practice. Take the non-optimum guiding system for example; it can be employed in the economic reform of the country’s macro policies, financial system as well as decision analysis. To be sure, the establishment of this non-optimum guiding system with computer as its means with information processing techniques as its foundation is no easy task.

The most obvious regulations lie in the economic system. The development degree of a country is shown not only by the change of its economic index. But also by the transit capacity from non-optimum to optimum.

Because the natures of the systems are different, their border are accordingly different. Of course, the border can change. From the viewpoint of the system’s transit regulation, the border is decided by the structure of the system. For example, the border of the optimum and non-optimum of the population system is decided by the synthetically system of the society and the economy. When the population increases to a certain extent, the national economy might keep a certain sustained development, or fluctuate to a certain level. When the population is under control, the national economy might leave the border situation for entering an optimal category. The economic system in the optimal category is called being in an interim. This border is different from the border mentioned before, which reflects that the non-optimum attribute is different from the optimal level.

Therefore, the border of the economic system and the transit time of the optimum are called the development time of the economic system. However, the aggregate non-optimum of the system will be in chaos, and then new attributes come into being, and part of the non-optimum of the system will accelerate its self-organization. Therefore, the non-optimum behavior and situation of the system contain versatile original dynamic energies, which are excavated, transferred, store and processed systematically in order to build up the non-optimum information system. Actually analysis shows that the advanced format of non-optimum information system can be actualized by the hardwares and softwares of the computer; the primary format can be composed of data, documents and diagrams. The primitive energy of the non-optimum information stored in the systematic database has broken through the limitation of the transit from physical sources to dynamic forces. As long as the states and behaviors of the non-optimum information exist, this energy always contains valid combustion value, and can form the dynamic forces accordingly at any time.

From the non-optimum analysis theory of systems, it can be concluded that people need the controllable order of the system, and non-optimum can also be more orderly. From the non-optimum reference system, the transit of the system from non-order into order as well as the requisites of the transit can be estimated. The non-optimum theory of systems will be widely used in the decision sciences. It can often transform people’s experiences into scientific means and might set up reference models with behavior attributes in the control system. This kind of model can marry the experiences and the theories, and can make actual judges to the running path of the system.

VI. CONCLUSIONS

The above is the overall description of the non-optimum problem of the system, which tells how to decide the overall frame-saw in the non-optimum system. However, different measurement and means have to be applied in different systems to solve actual problems. Proper quality and quantity determining methods are applied in the actual system analysis.

Furthermore, artificial intelligence and expert system reasoning tools can play important roles in non-optimum system analysis.

International Journal of Emerging Technology and Advanced Engineering

169 Because the borders change with objective conditions and subjective desire of mankind and human being has different behavior parameters, they always appear as uncertain under dynamic. Meanwhile, because of the continuous progress of mankind’s practice and recognition, under cooperating of the widely exchanged scientific information, the borders might become certain and describable during the dynamic changes. As to the judgment of the reasonability and accountability of the described borders, it is no a theoretical problem, but a problem of selecting the methods and checking the practice. In addition, when analyzing the problems of the system through quantitative methods, a lot of relationship parameters need to be statistically analyzed and attributably appraised. In many aspects, the influences of the system’s non-optimum are depended largely on the experience accumulated in the recognition of the system. That is to say, experiential analysis plays an important role in the non-optimum system analysis, which reflects the meaning and function of the combination of the nature and quantity evaluation.

We expect that the non-optimum thinking and the methods of non-optimum analysis on systems will grow into a new theoretical branch of decision theory that is system non-optimum analysis. Meanwhile, applying the theory and methods of information science and system engineering, the non-optimum thinking and the methods of non-optimum analysis on systems are still in their primitive stage of development and research as a new branch of learning, thinking and theory, But we believe that it will perfect and sophisticate the course of practice and debate, and will bring about results and gain its own position in the world of science.

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