Oleksandr AndriichenkoСОДЕРЖАНИЕ
2. PURPOSE AND OBJECTIVES OF THE DEVELOPMENT AND RESEARCH
4. REVIEW OF RESEARCH AND DEVELOPMENT
The survival and successful development of organization systems (organizations) in conditions of indeterminateness of the future (social, economical, political and ecological instability and intense competition) depends on the ability of management to predict possible trends in the situation and to generate appropriate strategies of the development of the organization. A striking example of the implementation of this ideology is the Balanced Scorecard (BS), which is well-known in the past decade. BS is focused on the identification of strategic factors - objectives and performance indicators, belonging to four groups: financial, customer, internal business processes, staff training and development, as well as to establish causal relationships between them. BS is dedicated by numerous (mostly economic) literature, the presentation of material in which is mostly on the descriptive level.
However, the number of papers is known to discuss the formal (mathematical) models and methods for describing and analyzing the development of “semistructured problem situations”, taking into account the “human factor” [1...9]. In these works the emphasis is on the formal apparatus of fuzzy cognitive maps (FCM) proposed by Kosko, although it’s effective to use other mathematical structures too. Creating an integrated formalism for the description and analysis of semistructured problematic situation (as BS contains blocks corresponding to this class of systems) filled the gap between the development of the BS and the formation of specific strategic plans of the organization [1]. Based on this unit have been developed a model of complex organizational systems in conditions of indeterminateness and semistructuring.
Balanced Scorecard (BS) provides the manager a tool to obtain the desired results in a complex competitive environment - the conditions in which all companies operate today. That is why a clear understanding of goals and objectives, as well as methods for their achievements and solutions is vital. The Balanced Scorecard, or criteria, considers the objectives and strategy of the company through the prism of a certain comprehensive evaluation of its activities, providing some methods to establish a system of strategic criteria and management systems. The focus of the BS is to assess the achievement of financial results, which are complemented by the financial performance of the immediate perpetrators. BS assesses the company's work on the basis of four balanced parameters: finances, relationships with customers, internal business processes, as well as training and staff development. Using BS one can analyze the financial results, but also participate in creating new opportunities and to regulate the acquisition of intangible assets for future growth.
The aim of this system is to forecast the development of complex organizational systems in conditions of indeterminateness and semistructuring (lack of objective information, which is partly replaced by subjective vision of an expert). Subjective vision is supported by a variety of mathematical tools, including the FCM.
Methodologies of analysis and forecasting using the FCM are focused mainly on the initial (preliminary) stage of designing new systems and long-term (strategic) planning of existing ones.
The task of creating this system is to determine the necessary changes in the organizational system, allowing to achieve the strategic objectives of the enterprise.
It’s necessary to create an expert analysis system of semistructured problem situations in organizational systems using fuzzy cognitive maps. Such a system will predict the development of complex organizational systems in conditions of uncertainty and semistructuring of (deficiency of objective information, which is partly replaced by a subjective vision of an expert).
It’s required to implement features that allow to monitor the achievement of strategic objectives enterprises to evaluate their performance, make adjustments in the management of the organization.
Developing system must solve two major problems:
- Analysis of total cross-impact, both directly and indirectly through intermediate factors (static analysis);
- Analysis of possible changes in the strategic factors of the system during the time interval of simulation.
The complex organization (corporation) is displayed by a set of interrelated submodels, which may correspond to situations of different types (partly good and partly semi-structured). It is planned to develop an expert system analysis of semistructured problem situations in organization systems. There will be used such types of graphs, as Petri nets, graphs increments and corresponding algorithms to work with them. Also, for finding solutions will be applied logic ambivalent relationship and its extension, called an interval ambivalent logic [1]. To determine the mutual interaction of factors is convenient to use dynamic causal logic. Given that in BS will be met as nice as poorly structured situations to adequately display the dynamics of the BS can use the triad model [10].
During the search among the works of masters DonNTU there were found the researches on the analysis of some organization systems (organizations) with a view to their improvement. There were used optimization methods. An example of such research is the work of Nadezhda Simin'ko. In addition DonNTU student Anastasiya Soboleva explored and developed the tools of cognitive modeling (one of the main tools to analyze organizational systems).
On the topic of the use of fuzzy cognitive maps for the analysis of organizational systems, studies were carried out by the following researchers: S. Yuditskii, I. Mouradian, L. Zheltova, V. Silov, O. Kuznetsov, A. Kulinich, A. Markovsky, V Kulba, B. Kosko, Liu Z.-Q., Zhang JY, Zhang WR. Chen S.S., Chen K.N.
Upon completion of the master work it is planned to implement an expert system analysis of semistructured problem situations in organizational systems using fuzzy cognitive maps. The software’s possibilities:
- Analysis of total cross-impact, both directly and indirectly through intermediate factors (static analysis);
- Analysis of possible changes in the strategic factors of the system on a time interval of simulation.
To achieve the first objective must be present such functions as:
- “Self-development” it’s when controlling factors are absent, and the status of the trust factor is determined by the initial conditions, passed through the appropriate chain to the cognitive map of situations;
- Direct simulation (defined by the reaction of the target factors to a given change in control);
- Inverse modeling (defined impact on the control factors that cause raised trends trust factors).
The work discusses models and methods that make up the formal framework of methodologies for analysis and forecasting of complex organizational systems in conditions of uncertainty and semistructuring. The subjective view is supported by various mathematical tools, including the FCM.
Methodologies for analysis and forecasting using the FCM are focused mainly on the initial (preliminary) stage of designing new systems and long-term (strategic) planning of existing ones. In applying the methodology are solving two main tasks:
- Analysis of total cross-impact, both directly and indirectly through intermediate factors (static analysis);
- Analysis of possible changes in the strategic factors in the time interval of simulation.
In static analysis there are determined the factors that are most strongly dependent on each other, and investigate the possibility of controlling tendencies of changes of some factors (target) through impacts on other more accessible factors (control). There are three options [7]:
- “Self-development” when controlling factors are absent, and the status of target factors is determined by initial conditions, transmitted through the appropriate chain to cognitive map of situations;
- Direct simulation (defined by the reaction of the target factors to a given change in control);
- Inverse modeling (defined impact on the control factors that cause raised trends trust factors).
The analysis of models and used methods (and potential applications) in the methodologies of static modeling semistructured situations is given.
Dynamic analysis of organizational systems development is a description of the approach based on the triad model [1]. The approach has the following features.
1. Triadic model is well structured: there is allocated an operating unit, which acts as coordinator of the process (modeled by a Petri net), there are the target and the estimated components (modeled on the basis of dynamic cognitive maps), the operational linkages between the blocks. The dimension of maps depicting the target and the estimated components are usually much smaller than the dimension maps for the system as a whole. This facilitates the expert weighting of cards - an assessment of the direction and strength of mutual interaction of factors.
2. The conception of the dynamic of the FCM is reseached, which is a graph of increments, in which:
- The positions correspond increment of factors, but a state of equilibrium is defined in a zero vector of increments;
- Interference effects are applied to map only in its equilibrium state;
- Interference effects initiate a map transition process, which culminates in the establishment of equilibrium (zero vector increments) before entering the next disturbance (stability condition).
The conditions of stability for some configurations of the graph increments are described. The question of necessary and sufficient conditions for stability of the graph of increments in the general case remains open.
There is researched a model of goal-setting in organizational systems, based on the integration mechanism to achieve the ultimate goals through the intermediate goals (event-driven Petri net “woody” form) and the mechanism of interference of the ultimate goals (count increments).
1. Юдицкий С. А., Мурадян И. А., Желтова Л. В. Анализ слабоструктурированных проблемных ситуаций в организационных системах с применением нечетких когнитивных карт// Приборы и системы. Управление, контроль, диагностика. 2007. № 7.
2. Kaплан P.С. Нортон Д. П. Сбалансированная система показателей. От стратегии к действию // Пер. с англ. М.: ЗАО «Олимп-Бизнес», 2003.
3. Робертс Ф.С. Дискретные математические модели с приложением к социальным, биологическим и экономическим задачам / Пер. с англ. М.: Наука, 1986.
4. Силов В.Б. Принятие стратегических решений в нечеткой обстановке. М.: Инпро-РЕС, 1995.
5. Кузнецов О.П., Кулинич А.А., Марковский А.В. Анализ влияний при управлении слабоструктурированными ситуациями на основе когнитивных карт // Человеческий фактор в управлении / Под ред. Н. А. Абрамовой, К.С. Гинсберга, Д.А. Новикова. М.: КомКиига, 2006.
6. Кульба В.В., Кононов Д.А., Косяченко С.А., Шубин А.Н. Методы формирования сценариев развития социально-экономических систем. М.: Синтег, 2004.
7. Максимов В.И. Структурно-целевой анализ развития социально-экономических ситуаций // Проблемы управления. 2005. № 3.
8. Kosko В, Fuzzy Cognitive Maps// International Journal of Man-Machine Studies. 1986. № 24.
9. Liu Z.-Q., Zhang J.Y. Interrogating the structure of fuzzy cognitive maps // Soft Computing. 2003. V.7.
10. Юдицкий С.А., Желтова Л.В., Мурадян И.А. Моделирование динамики развития конфигураций организационных систем на основе сетей Петри и графов приращений // Проблемы управления. 2007. № 6.
11. Корноушенко Е.К. Максимов В.И. Управление ситуацией с использованием структурных свойств её когнитивной карты // Тр. ИПУ РАН. 2000. T.XI.
12. Zhang W.R.. Chen S.S., Chen K.N. et al. On NPN logic. Proc. 18th IEЕЕ Internat. Symp. MVL, Palma de Mollora, Spain, 1988.
13. Zhang W.R., Chen S.S., Bezdek J.C. Pool2: A Generic System for Cognitive Map Development and Decision Analysis// IEEE Transactions On systems, Man, and Cybernetics. 1989. V.19. № 1.
14. Владиславлев П.Н., Мурадян И.А., Юдицкий С.А. Взаимодействие целевой и операционной динамических моделей сложных процессов // Автоматика и телемеханика. 2005. №11.
15. Юдицкий С.А. Моделирование динамики развития организационных систем // Автоматика и телемеханика. 2008. № 1.
16. Юдицкий С.А., Магергут В.З. Логическое управление дискретными процессами. М.: Машиностроение, 1987.
17. Юдицкий С.А, Радченко Е.Г. Алгебра потокособытий и сети Петри - язык потокового моделирования многоагентных иерархических систем // Приборы и системы. Управление, контроль, диагностика. 2004. № 9.
18. Питерсон Дж. Теория сетей Петри и моделирование систем / Пер с англ. М.: Мир, 1984.
19. Юдицкий С.А., Владиславлев П. Н. Основы предпроектного анализа организационных систем. М.: Финансы и статистика, 2005.
