Sadovnikova, N. P. Quality management of urban environment using the system dynamics method [Electronic resource] / N. P. Sadovnikova, D. S. Parygin, E. V. Manunina // Modern scientific research and their practical application. – 2013. – Is. 4 (J113). – Vol. J11307. – P. 176–182. – Mode of access : http://sworld.com.ua/e-journal/j11307.pdf
The formulation of strategies based on studying laws of urban development. Strategies allow purposely change life priorities and create new ways of organizing urban space. It provides effective interaction and balanced development of all spheres of life and city.
The only possible tool for studying these laws is modeling. Modeling does not guarantee complete protection against possible errors in decision making. But modeling allows identify the various problems and analyze the consequences decision-making.
To solve the problem of quality management of urban environment is necessary to identify the optimal set of control actions, which provide the required state parameters. In this case model experiments allow to estimate efficiency decision-making and trace dynamics of situations when implementing the different scenarios.
Modeling is one of the most appropriate methods by «price-quality» to study urban development laws. The need to consider many factors that reflect complex processes in economy, society, politics, and the level of technical innovation and management practices, for half a century facilitated the perpetration of modeling techniques. System Dynamics approach has been shown to be effective in solving problems in the semistructured spheres.
To obtain practically meaningful results in constructing models of urban development should consider the following points:
- described system is difficult to formalize;
- variety of factors (social, economic, environmental, etc.) create an environment where the action is very different laws, the integrated effect of which is difficult to predict;
- many relationships between elements of the system are difficult to quantify description;
- the initial information is heterogeneous and is usually contradictory;
- high level of uncertainty concepts, rules of behavior and properties that characterize the system;
- possibility of changing the structure and appearance of new systemic linkages;
- significant impact of human factors on all processes in the system.
Approaches to the use simulation modeling in solving problems management of social-economic systems, including city offered by J. Forrester, P. Davidson, D. Sterman, V. N. Sidorenko, N. N. Lychkina, V. A. Putilov, A. V. Gorokhov, D. YU. Katalevsky [1-6], etc. In various countries, particularly in Russia, there are national branch of the Society of system dynamics, annual international conference and journal «The System Dynamics Review» [7, 8]. There are many specialized systems designed for computer simulation modeling. They have a developed means for constructing models, conducting scenario calculations and analysis of simulation results.
The purpose of the functioning of urban ecosystem – to achieve a given quality of life while maintaining natural resource potential of development. Like any anthropogenic system, the urban ecosystem is not able to repair itself, but there is the possibility purposeful influence, which would allow forming the desired development trajectories.
Formal representation of the functioning of urban system can be set using the operator Ф that determines dependence:
with Q=(q1,q2,…,qs) – quality indicator system functioning (specially designated parameters of state, which determine the degree of goal achieving);
u(t)=(u1(t),u2(t)….uk(t)) – the input parameters (impacts that generated by control system);
v(t)=(v1(t),v2(t)….vl(t)) – the input parameters (uncontrolled impacts, random perturbations);
x(t)=(x1(t),x2(t)….xn(t)) – the current state of the urban environment;
у(t)=(y1(t),y2(t)….ym(t)) – output parameters describing the outcome executed actions.
The degree of stability is a common criterion for the efficiency of urban system, as well as the performance criteria of individual subsystems. Reaction the system to controlling influences depends on random factors, and the choice of control actions. Parameters of system state x(t) are related to input parameters by some operator F:
x(t)=F(x0, t, u[t0,t],v[t0,t]),
with x0=x(t0) – initial system state.
Method of forming control actions determines management strategy (way to allocate resources and management mechanisms). Specifing selection criteria of strategy, we obtain the problem of optimization of management. Given the complexity of the processes under study is difficult to identify a formal mathematical expression for this task. As a rule, the operator F can be represented as a set of interrelated actions. The criterion for selection strategy is to identify a set of indicators characterizing the achievement of objectives. So in this case is more applicable phrase «better management».
The problem of selecting operating influences is solved by decision maker with the assistance of expert consultants in various subject areas. The main function of a decision support system is related to the formation rules of selection decisions. Their application will allow to bring the system to commanded state. Unit operational management includes ongoing project management processes and procedures for monitoring the execution of decisions. At the strategic level decision-making processes can be structured in specific sequence of actions (fig.1). Thus, at the strategic level, decisions are made in the process of establishing management principles, and at the operational – in the selection process ways of using territory, distribution of funds, changing the conditions of economic management.
In the strategic management of any level actively use the System Dynamics modeling. This approach allows us not only simulate processes occurring in the studied system, but also give specific recommendations for improvement, both the structure and management practices. System Dynamics methodology is particularly effective in solving semistructured problems occurring in large systems with a significant number of feedbacks, material, financial and information flows.
The first step is to develop a conceptual model of the situation under study. Formed meaningful description studied system specifying the purpose of modeling and aspects of functioning the studied object that need to be studied with using simulation experiment. In this case, the purpose of modeling is to predict the anthropogenic load in the long term.
The model can be used for:
- approximate analysis of the existing dynamics and predict of anthropogenic load on the city territory;
- modeling consequences of different solutions;
- calculation environmental indicators.
Static description of the modeled system is performed during the structural analysis of the object. On the basis of statistical, analytical and expert information identifies the cause-effect relationships between factors. Also to structure the expert knowledge is constructed streaming charts.
For model construction using data published in the official information and reference portals [9, 10]. State of the city described by variables: population, production volume, environmental load, etc. External influences and management decisions determine the rate (the dynamics) of development the studied situation.
On the scheme at the top of the publication presents the model «Analysis of environmental load» that was constructed in system of Vensim .
Analyzed indicator is the environmental load. Considered the dynamics of this parameter in intervals of the 5 and 20 years of model time respectively.
As major regulators of the model stand out:
- nominal rates of environmental taxes (production and transport);
- volume of stimulating benefits on the introduction resource-saving technologies (production, utilities);
- environmental planning of territory development.
The proposed model allows to consider various options of development scenarios, compare different management strategies, and evaluate long-term effects of the current policy.
Implemented in the work simulation of anthropogenic load in conditions of city allowed compiling detailed static description of the modeled system, to conduct a structural analysis of the object and to identify key regulators of the model. Comparison of options strategic management allows better assessment of the long-term consequences of decisions. Obtained results are of practical interest for development of city environmental programs and choice of tax regulation ways.
- Forrester J. Urban Dynamics. – MIT Press, 1969; Portland, OR: Productivity Press, 1969. – 287 p.
- Sterman J.Business Dynamics: Systems Thinking and Modeling for a Complex World. – Boston: McGraw-Hill Companies, 2000.
- Lychkina N.N. Computer modeling of socioeconomic development of regions in decision support systems / Proceedings of the III International Conference «System Identification and Control Problems» SICPRO`04. – Moscow: ICS RAS, 2004.
- Sidorenko V.N. System Dynamics. – Moscow: MSU TEIS, 1998.
- Putilov V.A., Gorokhov A.V. System dynamics of regional development. – Murmansk: SIC «Pazori», 2002. – 306 p.
- Katalevskiy D.YU. Fundamentals of simulation modeling and system analysis in management. – Moscow: Publishing House of Moscow University, 2011. – 304 p.
- Site of the International community to system dynamics: http://www.systemdynamics.org
- Magazine site System Dynamics Review: http://onlinelibrary.wiley.com/journal/10.1002/%28ISSN%291099-1727
- Report on the environmental situation in the city of Volgograd region in 2010 [Electronic resource] / Administration of Volgograd Region. – 2010. – Access mode: http://oblkompriroda.volganet.ru/export/sites/oblkompriroda/folder_5/downloads/DOKLAD_2010_Verstka_12_shr.pdf
- Strategic Plan for Sustainable Development of Volgograd 2025 [Electronic resource] / Information portal of the city of Volgograd. – 2012. – Access mode: http://www.volgadmin.ru/ru/MPCity/StrategyPlanning.aspx
- Vensim Product Center Portal: http://www.vensim.com/