Weitere Kapitel dieses Buchs durch Wischen aufrufen
Movement towards more sustainable waste management practice has been identified as a priority in the whole of EU. The EU Waste Management Strategy’s requirements emphasize waste prevention; recycling and reuse; and improving final disposal and monitoring. In addition, in Hungary the national waste strategy requires an increase in the household waste recycling and recovery rates. Integrated waste management system (IWMS) can be defined as the selection and application of suitable and available techniques, technologies and management programs to achieve waste management objectives and goals. In this paper, the concept of ‘key drivers’ are defined as factors that change the status quo of an existing waste management system in either positive or negative direction. Due to the complexity and uncertainty occurring in sustainable waste management systems, we propose the use of fuzzy cognitive map (FCM) and bacterial evolutionary algorithm (BEA) methods to support the planning and decision making process of integrated systems, as the combination of the FCM and BEA seem to be suitable to model complex mechanisms such as IWMS. Since the FCM is formed for a selected system by determining the concepts and their relationships, it is possible to quantitatively simulate the system considering its parameters. The goal of optimization was to find such a connection matrix for FCM that makes possible to generate the most similar time series. This way a more objective description of IWMS can be given. While the FCM model represents the IWMS as a whole, BEA is used for parameter optimization and identification. Based on the results, in the near future we intend to apply the systems of systems (SoS) approach to regional IWMS.
Bitte loggen Sie sich ein, um Zugang zu diesem Inhalt zu erhalten
Sie möchten Zugang zu diesem Inhalt erhalten? Dann informieren Sie sich jetzt über unsere Produkte:
Bäck, T., Fogel, D. B., & Michalewicz, Z. (1997). Handbook of evolutionary computation. London: IOP Publishing and Oxford University Press.
Balázs, K., Botzheim, J., & Kóczy, L. T. (2010a). Comparison of various evolutionary and memetic algorithms. Integrated Uncertainty Management and Applications, Advances in Intelligent and Soft Computing, 68, 431–442. CrossRef
Balázs, K., Horváth, Z., & Kóczy, L. T. (2012). Different chromosome based evolutionary approaches for the permutation flow shop problem. Acta Polytechnica Hungarica, 2(2), 115–138.
Balázs, K., Kóczy, L. T., & Botzheim, J. (2010b). Comparative investigation of various evolutionary and memetic algorithms. In I. J. Rudas., J. Fodor., & J. Kacprzyk (Eds.), Computational intelligence in engineering, studies in computational intelligence (vol 313, pp. 129–140). Berlin: Springer.
Beigl, P., Lebersorger, S., & Salhofer, S. (2008). Modelling municipal solid waste generation: a review. Journal of Waste Management, 28, 200–214.
Botzheim, J., Földesi P., & Kóczy L. T. (2009b). Solution for fuzzy road transport travelling salesman problem using eugenic bacterial memetic algorithm. In Proceedings of IFSA/EUSFLAT Conference ‘2009 (pp. 1667–1672).
Bovea, M. D., & Powell, J. C. (2006). Alternative scenarios to meet the demands of sustainable waste management. Journal of Environmental Management, 79, 115–132. CrossRef
Buruzs, A., Hatwágner, M. F., Pozna, R. C., & Kóczy, L. T. (2013b). Advanced learning of fuzzy cognitive maps of waste management by bacterial algorithm. In Proceedings of IFSA World Congress and NAFIPS Annual Meeting (pp. 890–895). IEEE.
Buruzs, A., Pozna, R. C., & Kóczy, L. T. (2013a). Developing fuzzy cognitive maps for modelling regional waste management systems. In Y, Tsompanakis. (Ed.), Proceedings of the Third International Conference on Soft Computing Technology in Civil, Structural and Environmental Engineering, Paper 19. Stirlingshire, UK: Civil-Comp Press doi: 10.4203/ccp.103.19.
Carvalho, J. P. (2010). On the semantics and the use of fuzzy cognitive maps in social sciences. Soft Computing in the Humanities and Social Science, 214, 6–19. MathSciNet
Council Directive 1999/31/EC of April 26 1999 on the landfill of waste.
Dányádi, Zs, Balázs, K., & Kóczy, L. T. (2010a). A comparative study of various evolutionary algorithms and their combinations for optimizing fuzzy rule-based inference systems. Scientific Bulletin of “Politechnica” University of Timisoara, Romania, Transactions on Automatic Control and Computer Science 55(69), 247–254.
Dányádi, Zs., Földesi, P., & Kóczy, L. T. (2010b). A fuzzy bacterial evolutionary solution for three dimensional bin packing problems. Acta Technica Jaurinensis, Series Logistica, 3(3), 325–334.
Darwin, C. R. (1859). The origin of species. London: John Murray.
den Boer, E., & Lager, J. (2007). LCA-IWM: A decision support tool for sustainability assessment of waste management systems. Journal of Waste Management, 27(8), 1032–1045. CrossRef
Engelbrecht, A. P. (2007). Computational intelligence: An introduction. England: Wiley. CrossRef
European Parliament and Council Directive 94/62/EC of December 20, 1994 on packaging and packaging waste.
Gál, L., Botzheim, J., & Kóczy, L. T. (2008). Modified bacterial memetic algorithm used for fuzzy rule base extraction. In Proceedings of the 5th International of Conference on Soft Computing as Transdisciplinary Science and Technology (pp. 425–431). USA:ACM.
Goldberg, D. E. (1989). Genetic algorithms in search, optimization, and machine learning. Boston: Addison-Wesley Publishing Company, Inc.
Graymore, M. L. M., Sipe, N. G., & Rickson, R. E. (2008). Regional sustainability: how useful are current tools of sustainability assessment at the regional scale? Journal of Ecological Economics, 67(3), 362–372. CrossRef
Haastrup, P., Maniezzo, V., Mattarelli, M., Rinaldi, F. M., Mendes, I., & Paruccini, M. (1989). A decision support system for urban waste management. European Journal of Operational Research, 109(2), 330–341. CrossRef
Hatwágner, F. M., & Horváth, A. (2011). Parallel gene transfer operations for the bacterial evolutionary algorithm. Acta Technica Jaurinensis, 4(1), 89–112.
Hatwágner, F. M., & Horváth, A. (2012a). Comparative analysis of parallel gene transfer operators in the bacterial evolutionary algorithm. Acta Polytechnica Hungarica, 9(4), 65–84.
Hatwágner, F. M., & Horváth, A. (2012b). Maintaining genetic diversity in bacterial evolutionary algorithm. ANNALES Universitatis Scientiarum Budapestinensis de Rolando Eötvös Nominatae Sectio Computatorica 37, 175–194. MATH
Holland, J. H. (1975). Adaptation in natural and artificial systems. Ann Arbor: The University of Michigan Press.
Hung, M.-L., Ma, H.-W., & Yang, W.-F. (2007). A novel sustainable decision making model for municipal solid waste management. Journal of Waste Management, 27(2), 209–219. CrossRef
Isak, K. G. Q., Wildenberg, M., Adamescu, M., Skov, F., De Blust, G., & Varjopuro, R. (2009). A long-term biodiversity, ecosystem and awareness research network manual for applying fuzzy cognitive mapping—experiences from ALTER-Net. Project no. GOCE-CT-2003-505298, ALTER-Net Deliverable type: Report, WPR6-2009-02—Deliverable 4.R6.D2.
Jamshidi, M. (Ed.). (2009). Systems of system engineering. Innovation for the 21th century, 480 p. Wiley: Hoboken, ISBN 978-0-470-19590-1.
Kalakula, S., Malakulb, P., Siemanondb, K., & Gania, R. (2014). Integration of life cycle assessment software with tools for economic and sustainability analyses and process simulation for sustainable process design. Journal of Cleaner Production, 17, 98–109. CrossRef
Ketipi, M. K., Koulouriotis, D. E., Karakasis, E. G., Papakostas, G. A., & Tourassis, V. D. (2010). A flexible nonlinear approach to represent cause–effect relationships in FCMs. Journal of Applied Soft Computing, 12(12), 3757–3770. CrossRef
Kurian, J. (2006). Stakeholder participation for sustainable waste management. Journal of Habitat International, 30(4), 863–871. CrossRef
Langa, D. L., Binderb, C. R., Stauffachera, M., Zieglera, C., Schleiss, K., & Scholz, R. W. (2006). Material and money flows as a means for industry analysis of recycling schemes. A case study of regional bio-waste management. Journal of Resources, Conservation and Recycling, 49(06), 159–190. CrossRef
Malena, C. (2004). Strategic partnership: challenges and best practices in the management and governance of multi-stakeholder partnerships involving UN and civil society actors. Background paper prepared by for the multi-stakeholder workshop on partnerships and UN-civil society relations, Pocantico, New York.
Maniezzo, V., Mendes, I., & Paruccini, M. (1998). Decision support for siting problems. Journal of Decision Support Systems, 23(3), 273–284. CrossRef
McBean, E. A., del Rosso, E., & Rovers, F. A. (2005). Improvements in financing for sustainability in solid waste management. Journal of Resources, Conservation and Recycling, 43(4), 391–401. CrossRef
Morrissey, A. J., & Browne, J. (2004). Waste management models and their application to sustainable waste management. Journal of Waste Management, 24(3), 297–308. CrossRef
Nawa, N. E., & Furuhashi, T. (1998). A study on the effect of transfer of genes for the bacterial evolutionary algorithm. In L. C., Jain., & R. K., Jain (Eds.), Second international conference on knowledge-based intelligent electronic system Adelaide, Australia (pp. 585–590).
Nawa, N. E., & Furuhashi, T. (1999). Fuzzy system parameters discovery by bacterial evolutionary algorithm. IEEE Transactions on Fuzzy Systems, 7(5), 608–616. CrossRef
Nawa, N. E., Hashiyama, T., Furuhashi, T., & Uchikawa, Y. (1997). Fuzzy logic controllers generated by pseudo-bacterial genetic algorithm. In Proceedings of the IEEE International Conference of Neural Networks (ICNN97) Houston, USA (pp. 2408–2413).
Özesmi, U., & Özesmi, S. L. (2004). Ecological models based on people’s knowledge: A multi-step fuzzy cognitive mapping approach. Journal of Ecological Modelling, 176(15), 3–64.
Papageorgiou, E., & Kontogianni, A. (2012). Using fuzzy cognitive mapping in environmental decision making and management: A methodological primer and an application. In S. Young (Ed.), International perspectives on global environmental change. InTech doi: 10.5772/29375 ISBN: 978-953-307-815-1.
Perusich, K. (2010). System diagnosis using fuzzy cognitive maps. cognitive maps. InTech ISBN: 978-953-307-044-5.
Phillips, P. S., Read, A. D., Green, A. E., & Bates, M. P. (1999). UK waste minimisation clubs: A contribution to sustainable waste management. Journal of Resources, Conservation and Recycling, 27(3), 217–247. CrossRef
Salhofer, S., Wassermann, G., & Binner, E. (2007). Strategic environmental assessment as an approach to assess waste management systems. Experiences from an Austrian case study. Journal of Environmental Modelling and Software, 22(5), 610–618. CrossRef
Boardman J., & Sauser, B. (2009). System of systems—The meaning of. In Proceeding of the 2006 IEEE/SMC International Conference on System of Systems Engineering, Los Angeles, CA, USA.
Shmeleva, S. E., & Powell, J. R. (2006). Ecological–economic modelling for strategic regional waste management systems. Journal of Ecological Economics, 59(1), 115–130. CrossRef
Stylos, C. D., Georgopoulos, V. C., & Groumpos, P. P. (1997). The use of fuzzy cognitive maps in modelling systems. In Proceedings of 5th IEEE Mediterranean Conference on Control and Systems, Paphos, Cyprus.
Stylos, D., & Groumpos, P. P. (2004). Modelling complex systems using fuzzy cognitive maps. IEEE Transactions on Systems, Man, and Cybernetics—Part A: Systems and Humans, 34(1), 155–162.
Tanskanen, J.-H. (2000). Strategic planning of municipal solid waste management. Journal of Resources, Conservation and Recycling, 30(2), 111–133. CrossRef
Thorneloe, S. A., Weitz, K., Barlaz, M., & Ham, R. K. (1999). Tools for determining sustainable waste management through application of life-cycle assessment: Update on U.S. Research. In Proceedings of 7th International Waste Management and Landfill Symposium vol V, pp. 629–636.
van de Klundert, A., & Anschutz, J. (1999). Integrated sustainable waste management: The selection of appropriate technologies and the design of sustainable systems is not (only) a technological issue. CEDARE/IETC inter-regional workshop on technologies for sustainable waste management, pp. 1–17 Alexandria, Egypt.
Wilson, E. J., McDougall, F. R., & Willmore, J. (2001). Euro-Trash: Searching Europe for a more sustainable approach to waste management. Journal of Resources Conservation and Recycling, 31(4), 327–346.
Worku Y., & Muchie, M. (2012). An attempt at quantifying factors that affect efficiency in the management of solid waste produced by commercial businesses in the city of Tshwane, South Africa. Journal of Environmental and Public Health 2012, 12 p, Article ID 165353. doi: 10.1155/2012/165353 (research article).
- Expert-Based Method of Integrated Waste Management Systems for Developing Fuzzy Cognitive Map
Miklós F. Hatwágner
László T. Kóczy
Neuer Inhalt/© ITandMEDIA, Best Practices für die Mitarbeiter-Partizipation in der Produktentwicklung/© astrosystem | stock.adobe.com