Skip to main content
SpringerLink
Log in

Fuzzy Economic Analysis Methods for Environmental Economics

  • Chapter
  • First Online:
Intelligence Systems in Environmental Management: Theory and Applications

Part of the book series: Intelligent Systems Reference Library ((ISRL,volume 113))

Abstract

Environmental economics is an area of economics that studies the financial impact of environmental policies to determine the theoretical or empirical effects of these policies on the economy. In this chapter, engineering economy techniques are developed under fuzziness to be employed in environmental problems. Ordinary fuzzy sets, type-2 fuzzy sets , intuitionistic fuzzy sets , and hesitant fuzzy sets are handled in the development of fuzzy engineering economy analyses. For each of these fuzzy sets, an application related to environmental economics is given.

This is a preview of subscription content, log in via an institution to check access.

Access this chapter

Log in via an institution
Chapter
USD 29.95
Price excludes VAT (USA)
  • Available as PDF
  • Read on any device
  • Instant download
  • Own it forever
eBook
USD 129.00
Price excludes VAT (USA)
  • Available as EPUB and PDF
  • Read on any device
  • Instant download
  • Own it forever
Softcover Book
USD 169.99
Price excludes VAT (USA)
  • Compact, lightweight edition
  • Dispatched in 3 to 5 business days
  • Free shipping worldwide - see info
Hardcover Book
USD 169.99
Price excludes VAT (USA)
  • Durable hardcover edition
  • Dispatched in 3 to 5 business days
  • Free shipping worldwide - see info

Tax calculation will be finalised at checkout

Purchases are for personal use only

Institutional subscriptions

References

  • Ahman, M., & Holmgren, K. (2006). New entrant allocation in the Nordic energy sectors: Incentives and options in the EU ETS. Climate Policy, 6(4), 423–440.

    Article  Google Scholar 

  • Atanassov, K. (2012). On intuitionistic fuzzy sets theory. Berlin: Springer.

    Book  MATH  Google Scholar 

  • Atanassov, K. T. (1986). Intuitionistic fuzzy sets. Fuzzy Sets and Systems, 20, 87–96.

    Article  MathSciNet  MATH  Google Scholar 

  • Atanassova, L. (2008). On interval-valued intuitionistic fuzzy versions of L. Zadeh’s extension principle. Issues in Intuitionistic Fuzzy Sets and Generalized Nets, 7, 13–19.

    Google Scholar 

  • Azeez, K., Zayed, T., & Ammar, M. (2013). Fuzzy-versus simulation-based life-cycle cost for sewer rehabilitation alternatives. Journal of Performance of Constructed Facilities, 27(5), 656–665.

    Article  Google Scholar 

  • Baral, H., Keenan, R. J., Sharma, S. K., Stork, N. E., & Kasel, S. (2014). Economic evaluation of ecosystem goods and services under different landscape management scenarios. Land Use Policy, 39, 54–64.

    Article  Google Scholar 

  • Becker, N., Helgeson, J., & Katz, D. (2014). Once there was a river: A benefit-cost analysis of rehabilitation of the Jordan River. Regional Environmental Change, 14(4), 1303–1314.

    Article  Google Scholar 

  • Carrasco, L. R., & Papworth, S. K. (2014). A ranking of net national contributions to climate change mitigation through tropical forest conservation. Journal of Environmental Management, 146, 575–581.

    Article  Google Scholar 

  • Chen, D., Zhang, L., & Jiao, J. (2010). Triangle fuzzy number intuitionistic fuzzy aggregation operators and their application to group decision making. In F. L. Wang et al., (Eds.), AICI 2010, Part II, LNAI (Vol. 6320, pp. 350–357).

    Google Scholar 

  • Chen, S. J., Hwang, C. L., & Hwang, F. P. (1992). Fuzzy multiple attribute decision making: Methods and applications. Berlin: Springer.

    Book  MATH  Google Scholar 

  • Chinowsky, P. S., Price, J. C., & Neumann, J. E. (2013). Assessment of climate change adaptation costs for the U.S. road network. Global Environmental Change, 23(4), 764–773.

    Article  Google Scholar 

  • Chiu, C. Y., & Park, C. S. (1994). Fuzzy cash flow analysis using present worth criterion. The Engineering Economist, 39(2), 113–138.

    Article  Google Scholar 

  • Cooke, R., Wielicki, B. A., Young, D. F., & Mlynczak, M. G. (2014). Value of information for climate observing systems. Environment Systems and Decisions, 34(1), 98–109.

    Article  Google Scholar 

  • Dai, H., Sun, T., & Guo, W. (2016). Brownfield redevelopment evaluation based on fuzzy real options. Sustainability (Switzerland), 8(2), 170.

    Article  Google Scholar 

  • Duke, J. M., Dundas, S. J., Johnston, R. J., & Messer, K. D. (2014). Prioritizing payment for environmental services: Using nonmarket benefits and costs for optimal selection. Ecological Economics, 105, 319–329.

    Article  Google Scholar 

  • Espinoza, R. D., & Rojo, J. (2015). Using DNPV for valuing investments in the energy sector: A solar project case study. Renewable Energy, 75, 44–49.

    Article  Google Scholar 

  • Hanss, M. (2005). Applied fuzzy arithmetic: An introduction with engineering applications. Berlin: Springer.

    MATH  Google Scholar 

  • Hardisty, P. E., Sivapalan, M., & Humphries, R. (2013). Determining a sustainable and economically optimal wastewater treatment and discharge strategy. Journal of Environmental Management, 114, 285–292.

    Article  Google Scholar 

  • Jiang, L., Kronbak, J., & Christensen, L. P. (2014). The costs and benefits of sulphur reduction measures: Sulphur scrubbers versus marine gas oil. Transportation Research Part D: Transport and Environment, 28, 19–27.

    Article  Google Scholar 

  • Kahraman, C., Çevik Onar, S., & Öztayşi, B. (2015). Engineering economic analyses using intuitionistic and hesitant fuzzy sets. Journal of Intelligent & Fuzzy Systems, 29(3), 1151–1168.

    Article  MathSciNet  Google Scholar 

  • Kahraman, C., Onar, S. C., & Oztaysi, B. (2016). A comparison of wind energy investment alternatives using interval-valued intuitionistic fuzzy benefit/cost analysis. Sustainability (Switzerland), 8(2), 118.

    Article  Google Scholar 

  • Kahraman, C., Ruan, D., & Tolga, E. (2002). Capital budgeting techniques using discounted fuzzy versus probabilistic cash flows. Information Sciences, 142(1–4), 57–76.

    Article  MATH  Google Scholar 

  • Karnik, N. N., & Mendel, J. M. (2001). Centroid of a type-2 fuzzy set. Information Sciences, 132(1–4), 195–220.

    Article  MathSciNet  MATH  Google Scholar 

  • Kaufmann, A., & Gupta, M. M. (1988). Fuzzy mathematical models in engineering and management science. Amsterdam: Elsevier.

    MATH  Google Scholar 

  • Kumar, P. S., & Hussain, R. J. (2014). A method for solving balanced intuitionistic fuzzy assignment problem. International Journal of Engineering Research and Applications, 4(3), 897–903.

    Google Scholar 

  • Kunsch, P. L., & Vander Straeten, M. (2015). The cost of a nuclear-fuel repository: A criterion valuation by means of fuzzy logic. In Evaluation and decision models with multiple criteria: Case studies (p. 311). Berlin: Springer.

    Google Scholar 

  • Kuo-Ping, C. (2011). Multiple criteria group decision making with triangular interval type-2 fuzzy sets. In Proceedings of 2011 IEEE International Conference on Fuzzy Systems (FUZZ) (pp. 1098–7584) June 27–30, Taipei.

    Google Scholar 

  • Lia, C., Zhong, S., Duan, L., & Song, Y. (2011). Evaluation of petrochemical wastewater treatment technologies in Liaoning Province of China. Procedia Environmental Sciences, 10, 2798–2802.

    Article  Google Scholar 

  • Mahapatra, G. S., & Roy, T. K. (2009). Reliability evaluation using triangular intuitionistic fuzzy numbers arithmetic operations. World Academy of Science, Engineering and Technology, 3(2), 422–429.

    MathSciNet  Google Scholar 

  • Milanesi, G. S., Broz, D., Tohmé, F., & Rossit, D. (2014). Strategic analysis of forest investments using real option: The fuzzy pay-off model (FPOM). Fuzzy Economic Review, 19(1), 33–44.

    Google Scholar 

  • Nepal, P., Ince, P. J., Skog, K. E., & Chang, S. J. (2013). Forest carbon benefits, costs and leakage effects of carbon reserve scenarios in the United States. Journal of Forest Economics, 19(3), 286–306.

    Article  Google Scholar 

  • Niewiadomski, A., Ochelska, J., & Szczepaniak, P. S. (2006). Interval-valued linguistic summaries of databases. Control and Cybernetics, 35(2), 415–443.

    MATH  Google Scholar 

  • Petković, D., Shamshirband, S., Kamsin, A., Lee, M., Anicic, O., & Nikolić, V. (2016). Survey of the most influential parameters on the wind farm net present value (NPV) by adaptive neuro-fuzzy approach. Renewable and Sustainable Energy Reviews, 57, 1270–1278.

    Article  Google Scholar 

  • Quintero, A., Konare, D., & Pierre, S. (2005). Prototyping an intelligent decision support system for improving urban infrastructures management. European Journal of Operational Research, 162(3), 654–672.

    Article  MATH  Google Scholar 

  • Ross, T. J. (1995). Fuzzy logic with engineering applications. USA: McGraw-Hill.

    MATH  Google Scholar 

  • Shamshirband, S., Petković, D., Ćojbašić, Ž., Nikolić, V., Anuar, N. B., Mohd Shuib, N. L., et al. (2014). Adaptive neuro-fuzzy optimization of wind farm project net profit. Energy Conversion and Management, 80, 229–237.

    Article  Google Scholar 

  • Sharda, V. N., Dogra, P., & Sena, D. R. (2015). Comparative economic analysis of inter-crop based conservation bench terrace and conventional systems in a sub-humid climate of India. Resources, Conservation and Recycling, 98, 30–40.

    Article  Google Scholar 

  • Sheen, J. N. (2009). Applying fuzzy engineering economics to evaluate project investment feasibility of wind generation. WSEAS Transactions on Systems, 8(4), 501–510.

    Google Scholar 

  • Sheen, J. N. (2014a). Valuing wind power project on renewable electricity whole-sale tariff in power market. Applied Mechanics and Materials, 483, 664–667.

    Article  Google Scholar 

  • Sheen, J. N. (2014b). Real option analysis for renewable energy investment under uncertainty. Lecture Notes in Electrical Engineering, 293, 283–289.

    Article  Google Scholar 

  • Sheley, R., Sheley, J., & Smith, B. (2014). Cost/benefit analysis of managing invasive annual grasses in partially invaded sagebrush steppe ecosystems. Weed Science, 62(1), 38–44.

    Article  Google Scholar 

  • Singh, S., & Mishra, A. (2014). Deforestation-induced costs on the drinking water supplies of the Mumbai metropolitan. India Global Environmental Change, 27(1), 73–83.

    Article  Google Scholar 

  • Tim Chamen, W. C., Moxey, A. P., Towers, W., Balana, B., & Hallett, P. D. (2015). Mitigating arable soil compaction: A review and analysis of available cost and benefit data. Soil and Tillage Research, 146, 10–25.

    Article  Google Scholar 

  • Torra, V. (2010). Hesitant fuzzy sets. International Journal of Intelligent Systems, 25(6), 529–539.

    MATH  Google Scholar 

  • Uçal Sarı, I., & Kahraman, C. (2015). Interval type-2 fuzzy capital budgeting. International Journal of Fuzzy Systems, 17(4), 635–646.

    Article  MathSciNet  Google Scholar 

  • Vahdat-Aboueshagh, H., Nazif, S., & Shahghasemi, E. (2014). Development of an algorithm for sustainability based assessment of reservoir life cycle cost using fuzzy theory. Water Resources Management, 28(15), 5389–5409.

    Article  Google Scholar 

  • Wicke, B., Smeets, E. M. W., Akanda, R., Stille, L., Singh, R. K., Awan, A. R., et al. (2013). Biomass production in agroforestry and forestry systems on salt-affected soils in South Asia: Exploration of the GHG balance and economic performance of three case studies. Journal of Environmental Management, 127, 324–334.

    Article  Google Scholar 

  • Winans, K. S., Tardif, A.-S., Lteif, A. E., & Whalen, J. K. (2015). Carbon sequestration potential and cost-benefit analysis of hybrid poplar, grain corn and hay cultivation in southern Quebec, Canada. Agroforestry Systems, 89(3), 421–433.

    Article  Google Scholar 

  • Wolf, K. L., Measells, M. K., Grado, S. C., & Robbins, A. S. T. (2015). Economic values of metro nature health benefits: A life course approach. Urban Forestry and Urban Greening, 14(3), 694–701.

    Article  Google Scholar 

  • Xia, M. M., & Xu, Z. S. (2011). Hesitant fuzzy information aggregation in decision making. International Journal Approximate Reasoning, 52, 395–407.

    Article  MathSciNet  MATH  Google Scholar 

  • Xu, Z.-S. (2007). Methods for aggregating interval-valued intuitionistic fuzzy information and their application to decision making. Control and Decision, 22(2), 215–219.

    Google Scholar 

  • You, L., Li, Y. P., Huang, G. H., & Zhang, J. L. (2014). Modeling regional ecosystem development under uncertainty—A case study for New Binhai District of Tianjin. Ecological Modelling, 288, 127–142.

    Article  Google Scholar 

  • Yu, D. (2013). Triangular hesitant fuzzy set and its application to teaching quality evaluation. Journal of Information & Computational Science, 10(7), 1925–1934.

    Article  Google Scholar 

  • Zadeh, L. A. (1965). Fuzzy sets. Information and Control, 8(3), 338–353.

    Article  MathSciNet  MATH  Google Scholar 

  • Zadeh, L. A. (1974). Fuzzy logic and its application to approximate reasoning. Information Processing, 74, 591–594.

    MathSciNet  MATH  Google Scholar 

  • Zadeh, L. A. (1975). The concept of a linguistic variable and its application to approximate reasoning—I. Information Sciences, 8(3), 199–249.

    Article  MathSciNet  MATH  Google Scholar 

  • Zhang, Y., White, M. A., & Colosi, L. M. (2013). Environmental and economic assessment of integrated systems for dairy manure treatment coupled with algae bioenergy production. Bioresource technology, 130, 486–494.

    Article  Google Scholar 

  • Zhao, H., & Guo, S. (2015). External benefit evaluation of renewable energy power in China for sustainability. Sustainability (Switzerland), 7(5), 4783–4805.

    Article  Google Scholar 

Download references

Author information

Authors and Affiliations

  1. Industrial Engineering Department, Management Faculty, Istanbul Technical University, Macka, Istanbul, Turkey

    Cengiz Kahraman, İrem Uçal Sarı, Sezi Cevik Onar & Basar Oztaysi

Authors
  1. Cengiz Kahraman
    View author publications

    You can also search for this author in PubMed Google Scholar

  2. İrem Uçal Sarı
    View author publications

    You can also search for this author in PubMed Google Scholar

  3. Sezi Cevik Onar
    View author publications

    You can also search for this author in PubMed Google Scholar

  4. Basar Oztaysi
    View author publications

    You can also search for this author in PubMed Google Scholar

Corresponding author

Correspondence to Cengiz Kahraman .

Editor information

Editors and Affiliations

  1. Fac. Management, Dept of Industrial Engg, Istanbul Technical University, Istanbul, Turkey

    Cengiz Kahraman

  2. Magt Facu, Department of Industrial Engd, Istanbul Technical University, Istanbul, Turkey

    İrem Uçal Sari

Rights and permissions

Reprints and permissions

Copyright information

© 2017 Springer International Publishing Switzerland

About this chapter

Cite this chapter

Kahraman, C., Sarı, İ.U., Onar, S.C., Oztaysi, B. (2017). Fuzzy Economic Analysis Methods for Environmental Economics. In: Kahraman, C., Sari, İ. (eds) Intelligence Systems in Environmental Management: Theory and Applications. Intelligent Systems Reference Library, vol 113. Springer, Cham. https://doi.org/10.1007/978-3-319-42993-9_14

Download citation

  • DOI: https://doi.org/10.1007/978-3-319-42993-9_14

  • Published:

  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-319-42992-2

  • Online ISBN: 978-3-319-42993-9

  • eBook Packages: EngineeringEngineering (R0)

Publish with us

Policies and ethics

Search

Navigation