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FOUNDATIONS OF CIVIL AND ENVIRONMENTAL ENGINEERING

No. 6

2005

Edmundas Kazimieras ZAVADSKAS1, Arturas KAKLAUSKAS2, Jonas SAPARAUSKAS3 1,2 Vilnius Gediminas Technical University Department of Building Technology and Management 3 Vilnius Gediminas Technical University Department of Construction Economics and Property Management

SUSTAINABLE URBAN DEVELOPMENT AND WEB-BASED MULTIPLE CRITERIA ANALYSIS

The analysis of information, expert and decision support systems used in sustainable urban development that were developed by researchers from various countries assisted the authors in the creation of their own Sustainable Urban Development Decision Support System (SUD-DSS). SUD-DSS differs from other systems in the use of new multiple criteria analysis methods as were developed by the authors. The database of a sustainable urban development was developed providing a comprehensive assessment of alternative versions from the economic, political, legal, social, management, technical, technological and other points of view. Based on the above complex databases, the developed SUD-DSS enables the user to analyse alternatives quantitatively (i.e. a system and subsystems of criteria, units of measure, values and weights) and conceptually (i.e. the text, formula, schemes, graphs, diagrams and videotapes).

Key words: Sustainable urban development, strategies, decision support systems, multiple criteria analysis

1. INTRODUCTION Sustainable urban development has different approaches and different priorities in different countries. It is not surprising that there are widely divergent views and interpretations among various countries, with marked differences between countries with developed market economies, those with © Publishing House of Poznan University of Technology, PoznaĔ 2005 ISSN 1642-9303

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transition economies and developing countries. Not all countries with one of the three development levels, understand sustainable urban development in the same way thus, having different strategies. Developing countries have different environmental and socio-economic systems than most developed countries. Climatic circumstances and geographic conditions have a distinct impact on the features of the ecosystems. Many developing countries possess highly diversified but fragile ecosystems. Moreover, developing countries are still predominantly rural, whereas the developed world is largely urbanized.

2. SUCCESSFUL STRATEGY FOR SUSTAINABLE URBAN DEVELOPMENT As successful strategy for sustainable urban development should be more or less compatible with political, economic, social, cultural, and other situations of an examined country. A varied spectrum of strategies can be launched, while keeping in mind that the mix of influencing factors and relative emphasis is put on some of those factors and overall outcome will depend on local conditions.The best sustainable urban development strategy of another country cannot just be copied. Strategies may only be adapted into a real economic, social, political, legislation/regulation and provision situations of an existing state. There is no such thing as a single sustainable urban development strategy to suit all societies that could be applied to all countries.

3. SUSTAINABLE DEVELOPMENT AUTOMATION APPLICATIONS Major players in a sustainable development can use calculators, analyzers, software, neural networks, expert and decision support systems, etc. Calculators A calculator is a software application that is used for completing mathematical calculations. Calculators range from very cheap software, capable of performing basic arithmetical operations, to those whose capabilities extend to sophisticated mathematical and statistical manipulations and those that may be programmed with a large number of steps. Web sites sometimes contain sustainable development calculators [15]. Software Interested parties also use software with various purposes as listed below: Rural/Urban Projection (RUP) Program [16]; atmospheric pollution, energy economics, indoor air quality, multi-building facilities, solar/climate analysis,

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training, utility evaluation, validation tools, ventilation/airflow and water conservation [17]. Decision support systems Major sustainable development players can use various purpose decision support systems [12]. The decision support system (DSS) provides a framework through which decision-makers can obtain the necessary assistance needed for making decisions through an easy-to-use menu or command system. Generally, a DSS will provide help in formulating alternatives, accessing data, developing models and interpreting their results and by selecting options or analyzing the impacts of a selection. Expert systems Expert systems today generally serve to relieve a ‘human’ professional of some of the difficult but clearly formulated tasks. For example, expert system can provide global information to the human society and find possibilities of policy coordination among countries in order to achieve sustainable development of the world economy [10]. Neural networks Neural network is a method of computing that tries to copy the way the human brain works. A group of processing elements receives data and at the same time links are made between the elements as the repeated patterns are recognized [1, 2, 4, 6, 8, 13].

4. THE DATABASE OF THE BEST PRACTICE Today information technologies are rapidly expanding throughout all spheres of activities. Large amounts of information are stored and databases are created, on the basis of which thousands of high quality experts pass on their experiences and expertise through the Internet. The database of the best practice can be formed by studying the expertise of advanced industrial economies. In order to effectively analyse a database of best practice regarding sustainable urban development and to prepare recommendations for cities under consideration, it is essential to find the best research methods and analysis tools. In this proposal, the aim was to direct the research methods and analysis tools (Multiple Criteria Analysis, Life Cycle Analysis; etc.) for assessing and implementing the goals of sustainable urban development.

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5. DECISION MAKING MODELS AND MULTIPLE CRITERIA ANALYSIS A thorough sustainable urban development evaluation is quite difficult to undertake, because a city and its environment are complex systems (compatible with political, economic, social, cultural, institutional, technological, environmental, legal/regulatory, education situation systems, etc.) where all subsystems influence the total efficiency performance and where the interdependence between sub-systems play a significant role. Multi-variant design and multiple criteria analysis can be undertaken to develop and select the effective alternatives: • Air quality, noise, traffic, pedestrians, evacuation and catastrophy management, etc. • Energy conservation measures, water and drainage initiatives and transport strategies. • Construction and sustainable housing modernisation alternatives (amount of materials, energy and labour needed for construction, heating energy consumption, etc.). • Alternatives of subsidies and taxation, etc. Many decision making models and methods have been developed in the world for solving the above mentioned and other problems [3, 9, 11].

6. WEB-BASED SUSTAINABLE URBAN DEVELOPMENT MULTIPLE CRITERIA DECISION SUPPORT SYSTEM (SUD-DSS) Based on the analysis of existing information, neural networks, expert and decision support systems and in order to determine best practice of sustainable urban development and to prepare recommendations for countries under consideration a Sustainable Urban Development Decision Support System consisting of a database, database management system, model-base, model-base management system and user interface were developed. The developed Sustainable Urban Development Decision Support System (SUD-DSS) includes models enabling a decision maker to make a comprehensive analysis of the available sustainable urban development variants and then make the best choice for cities under consideration. Alternatives The more alternative versions investigated before making a final decision, the greater the possibility to achieve a more rational final result. Based on a sustainable urban development database available and the decision support

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system, it is possible to perform a multiple criteria analysis of sustainable urban development components and select the most efficient versions for the particular country. Stakeholders’ (urban planners, city administrators, elected representatives, architects, public or corporate owners of flats, etc.) decisions can increase or decrease the efficiency of alternatives. The developed Web-based sustainable urban development decision support system should integrate multiple points of view and enable the collaboration of different stakeholders that are involved in this process. Multivariant design and multiple criteria analysis Analytical model of sustainable urban development developed by VGTU enables a decision-maker to develop alternatives, perform a comprehensive analysis of the available variants and make a proper choice. The more alternative versions that are investigated before making a final decision, the greater the possibility to achieve a more rational final result. Based on the collected information it is possible to perform a multiple criteria analysis of the components of the said development. Having performed a multiple criteria analysis of the full sustainable urban development process in this way, one can select the most efficient versions. Selection and adaptation of good practices to fit the local/regional circumstances Every time countries use a sustainable urban development database they may make corrections to the database according to the aims to be achieved and the available situation. For example, a given city considers economic sustainability to be more important than social sustainability, while other cities may be of the opposite opinion. The city striving to express its attitude towards these issues numerically may ascribe various significance values to them, which will eventually affect the general estimation of a sustainable urban development. Though this assessment may seem biased and even quite subjective, the solution finally made may exactly meet the requirements, aims and affordability of the city under consideration. Database The presentation of information needed for decision-making in the SUDDSS may have a conceptual form (i.e. digital/numerical, textual, graphicdiagrams, graphs and drawing, etc.) or other forms such as photographic, sound, video as well as quantitative. The presentation of quantitative information involves criteria systems and subsystems, units of measurement, values and initial weights that fully define the provided variants. Conceptual information means a conceptual description of the alternative solutions, the criteria and ways of determining their values and the weights, etc. (see Fig. 1). Hence, the SUDDSS enables the decision-maker to receive various conceptual and quantitative information on sustainable urban development from a database and a model-base allowing him/her to analyse the above factors and to form an efficient solution.

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Fig. 1. The presentation of quantitative information in the SUD-DSS (integrated assessment for sustainability appraisal in cities and regions)

Model-base and models The efficiency of a sustainable urban development variant is often determined by considering many factors. The model-base of a decision support system should include models that enable a decision-maker to do a comprehensive analysis of the available variants and to make a proper choice. Models-base According to the user’s needs, various models may be provided by a model management system. When a certain model (i.e. search for sustainable urban development alternatives) is used, the results obtained become the initial data for some other models (i.e. a model for multiple criteria analysis and setting the priorities). The results of the latter, in turn, may be taken as the initial data for some other models (i.e. determination of the degree of usability of sustainable urban development). Models Since the analysis of sustainable urban development is usually performed by considering many factors, a model-base should include models which will enable a decision-maker to carry out a comprehensive analysis of the available variants and make a proper choice. The following multiple criteria analysis methods and models as developed by the authors [7, 14] are used by the SUDDSS in the analysis of the sustainable urban development alternatives: a new method and model of complex determination of the importance of the criteria taking into account their quantitative and qualitative characteristics were developed. A new method and model of multiple criteria complex proportional evaluation of projects enabling the user to obtain a reduced criterion determining

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the complex (overall) efficiency of the project was suggested (see Fig. 2 and Fig. 3).

Fig. 2. Example - Integrated assessment for sustainability appraisal in cities and regions

Fig. 2. Example - analysis of sustainable economic structures



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7. CONCLUSIONS The analysis of information, the expert and decision support systems, neural networks used in sustainable development that were developed by researchers from various countries assisted the authors in creating of their own Web-Based Sustainable Urban Development Multiple Criteria Decision Support System (SUD-DSS). The initial database of a sustainable urban development was developed providing a comprehensive assessment of alternative versions from the political, economic, social, cultural, institutional, technological, environmental, legal/regulatory, educational points of view. Based on the above initial database, the developed SUD-DSS enables the user to analyse the alternatives quantitatively (i.e. a system and subsystems of criteria, units of measure, values and weights) and conceptually (i.e. the text, formula, schemes, graphs, diagrams and videotapes). The efficiency of calculators, analysers, software, neural networks, expert and decision support systems may be increased by applying SUD-DSS.

REFERENCES 1. Buch A. M., Mazumdar H. S. and Pandey P. C.: Application of artificial neural networks in hydrological modelling – a case study of run-off simulation of Himalayan glacier basin, presented at International Joint Conference on Neural Networks, Nagoya, Japan, 1993. 2. Cote M., Grandjean B. P. A., Lessard P. and Thibault J.: Dynamic modelling of the activated sludge process: improving prediction using neural networks, Water Research, 29, 4 (1995) 995-1004. 3. Ferng J. J.: Toward a scenario analysis framework for energy footprints, Ecological Economics, 40, 1, (2002) 53-69. 4. Furuta H., Tonegawa T. and Watanabe E.: Application of neural computing to aesthetic design of dam structures, in: Proceedings of the 2nd International Conference of Fuzzy Logic and Neural Networks (IIZUKA'92), Vol. 2, 1992, 851-854. 5. Gallez C.: Indicators for comparing prospective scenarios. Can we broaden the urban travel debate?, Recherce – Transports – Securite, 2000. 6. Ichikawa R., Nishimura K., Kunugi M., Shimada K., Shimakura Y. H. Fujisawa Y. and Matsunoki Y.: Auto-tuning method of fuzzy memberships functions using neural network learning algorithm: application to water flow forecasting for reservoir, in: Proceedings of the 2nd International Conference of Fuzzy Logic and Neural Networks (IIZUKA'92), Vol. 2, 1992, 894-898.

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7. Kaklauskas A., Zavadskas E. K.: Web-based decision support, Vilnius, Technika 2002. 8. Khanna P., Babu P. R., George M. S.: Carrying-capacity as a basis for sustainable development. A case study of National Capital Region in India, Progress in Planning, 52, 2 (1999) 101-163. 9. Nijkamp P., Vreeker R.: Sustainability assessment of development scenarios: methodology and application to Thailand, Ecological Economics, 33, 1 (2000) 7-27. 10. Onishi A.: FUGI global modeling system (FGMS200). Integrated global model for sustainable development, Journal of Policy Modeling, 24, 6 (2002) 561-590. 11. Rotmans J., Asselt M., Anastasi C., Greeuw S., Mellors J., Peters S., Rothman D., Rijkens N.: Visions for a sustainable Europe, Futures, 32, 9-10 (2000) 809-831. 12. Rylatt M., Gadsden S., Lomas K.: GIS-based decision support for solar energy planning in urban environments, Computers, Environment and Urban Systems, 25, 6 (2001) 579-603. 13. Yuan J. L. and Fine T. I.: Forecasting demand for electric power, Editors J. D. Cewan and C. L. Giles, Moregan Kanffman, San Matteo, 1993. 14. Zavadskas E.K., Simanauskas L., Kaklauskas A.: Decision support systems in construction, Vilnius, Technika 1998. 15. http://sun2.lib.uci.edu/~martindale/RefCalculators.html 16. http://www.eere.energy.gov/buildings/tools_directory/subject.html 17. http://www.census.gov/ipc/www/rup.html

E. K. Zavadskas, A. Kaklauskas, J. Saparauskas HARMONIJNY ROZWÓJ MIASTA A WIELOKRYTERYJNA ANALIZA INTERNETOWA Streszczenie Strategia harmonijnego rozwoju konkretnego miasta nie moĪe byü Ğlepo naĞladowana. MoĪe ona jedynie byü dostosowywana do warunków ekonomicznych, spoáecznych, politycznych, prawny i innych. Nie istnieje jakaĞ uniwersalna strategia harmonijnego rozwoju miasta pasująca dla jakiegokolwiek spoáeczeĔstwa lub kraju. Analiza systemów wspierania decyzji informacyjnych, ekspertowych utworzonych przez naukowców z róĪnych krajów pobudziáa autorów do stworzenia swojego systemu wspierania decyzji harmonijnego rozwoju miasta (SWDHRM). System ten od innych systemów róĪni siĊ tym, Īe są w nim stosowane nowe, stworzone przez

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autorów metody analizy wielowymiarowej. TakĪe zostaáa stworzona baza danych mogąca sáuĪyü do szczegóáowej oceny perspektyw ekonomicznych, politycznych, prawnych, spoáecznych, zarządczych, technologicznych oraz ich wersji. Przy uĪyciu wspomnianej bazy danych w utworzonym SWDHRM moĪna przeprowadzaü iloĞciową i jakoĞciową analizĊ kolejnych wersji. Received, 18.02.2004.