Environmental Earth Sciences

, Volume 72, Issue 1, pp 221–231 | Cite as

Application of fuzzy multi-attribute decision-making to select and to rank the post-mining land-use

  • Isa MasoumiEmail author
  • Saeed Naraghi
  • Farshad Rashidi-nejad
  • Shiba Masoumi
Original Article


The selection of an optimal reclamation method is one of the most important portions of the surface mining design. There are many factors in this problem which seriously influence decision-making. The fuzzy set theory was applied due to the effect of uncertain parameters involved in the decision-making process. Therefore, the fuzzy multi-attribute decision-making method was proposed. The aim of this study is to use the fuzzy technique for order preference by similarity to ideal solution method for ranking the optimal post-mining land-use and the fuzzy analytic hierarchy process method in order to determine the weights of each criterion. This approach is applied to the surface coal mine by employing 28 criteria which influence the decision-making procedure. The TOPSIS and AHP methods have been the most used methods of mining decision-making and demonstrated their ability to make critical decisions. By evaluating the alternatives and considering effective criteria with proposed methods, agriculture is the optimal post-mining land-use.


Fuzzy analytic hierarchy process Fuzzy technique for order preference by similarity to ideal solution Limiting method Mined land reclamation Post-mining land-use 


  1. Akbari AD, Osanloo M, Hamidian H (2006) Selecting post mining land use through analytical hierarchy processing method: case study in Sungun copper open pit mine of Iran. 15th international symposium of MPES, Torino, Italy, pp 245–252Google Scholar
  2. Alexander MJ (1996) The effectiveness of small-scale irrigated agriculture in the reclamation of mine land soils on the Jos Plateau of Nigeria. Land Degrad Dev 7(1):77–85CrossRefGoogle Scholar
  3. Bascetin A (2007) A decision support system using analytical hierarchy process (AHP) for the optimal environmental reclamation of an open-pit mine. Environ Geol 52:663–672CrossRefGoogle Scholar
  4. Bazzazi AA, Osanloo M, Soltanmohammadi H (2008) Loading-haulage equipment selection in open pit mines based on fuzzy-TOPSIS method. Gospodarka Surowcami Mineralnymi 24:87–102Google Scholar
  5. Bazzazi AA, Osanloo M, Karimi B (2011) Deriving preference order of open pit mines equipment through MADM methods: application of modified VIKOR method. Expert Syst Appl 38:2550–2556CrossRefGoogle Scholar
  6. Bielecka M, Krol-Korczak J (2010) Hybrid expert system aiding design of post-mining regions restoration. Ecol Eng 36:1232–1241CrossRefGoogle Scholar
  7. Cakir O (2008) On the order of the preference intensities in fuzzy AHP. Comput Ind Eng 54:993–1005CrossRefGoogle Scholar
  8. Calo F, Parise M (2009) Waste management and problems of groundwater pollution in karst environments in the context of a post-conflict scenario: the case of Mostar (Bosnia Herzegovina). Habitat Int 33:63–72CrossRefGoogle Scholar
  9. Cao X (2007) Regulating mine land reclamation in developing countries: the case of China. Land Use Policy 24:472–483 CrossRefGoogle Scholar
  10. Carrick PJ, Kruger R (2007) Restoring degraded landscapes in lowland Namaqualand: lessons from the mining experience and from regional ecological dynamics. J Arid Environ 32:52–67Google Scholar
  11. Chang DY (1996) Applications of the extent analysis method on fuzzy AHP. Eur J Oper Res 95:649–655CrossRefGoogle Scholar
  12. Chen CT (2000) Extensions of the TOPSIS for group decision-making under fuzzy environment. Fuzzy Sets Syst 114:1–9CrossRefGoogle Scholar
  13. Chen CT, Lin CT, Huang SF (2006) A fuzzy approach for supplier evaluation and selection in supply chain management. Int J Prod Econ 102:289–301CrossRefGoogle Scholar
  14. Demirel T, Demirel NC, Kahraman C (2008) Fuzzy analytic hierarchy process and its application. In: Kahraman C (ed) Fuzzy multi-criteria decision making. Springer Science+Business Media LLC, New York, pp 53–83CrossRefGoogle Scholar
  15. Deng H (1999) Multicriteria analysis with fuzzy pair-wise comparison. Int J Approx Reason 21:215–231CrossRefGoogle Scholar
  16. Ertugrul I, Karakasoglu N (2007) Comparison of fuzzy AHP and fuzzy TOPSIS methods for facility location selection. Int J Adv Manuf Technol 39(7–8):783–795Google Scholar
  17. Gizikoff KG (2004) Re-establishing livestock use on mined landscapes in the southern interior of BC. Available online:
  18. Gligoric Z, Beljic C, Simeunovic V (2010) Shaft location selection at deep multiple ore body deposit by using fuzzy TOPSIS method and network optimization. Expert Syst Appl 37(2):1408–1418Google Scholar
  19. Golestanifar M, Bazzazi AA (2010) TISS: a decision framework for tailing impoundment site selection. Env Earth Sci 61:1505–1513CrossRefGoogle Scholar
  20. Hwang CL, Yoon K (1981) Multiple attributes decision making methods and applications. Springer, BerlinCrossRefGoogle Scholar
  21. Kahraman C, Cebeci U, Ruan D (2004) Multi-attribute comparison of catering service companies using fuzzy AHP: the case of Turkey. Int J Prod Econ 87:171–184CrossRefGoogle Scholar
  22. Langholtz M, Carter DR, Rockwood DL, Alavalapati JRR (2007) The economic feasibility of reclaiming phosphate mined lands with short-rotation woody crops in Florida. J For Econ 12:237–249Google Scholar
  23. Li MS (2006) Ecological restoration of mineland with particular reference to the metalliferous mine wasteland in China: a review of research and practice. Sci Total Environ 357:38–53CrossRefGoogle Scholar
  24. Li X, Wang K, Liu L, Xin J, Yang H, Gao C (2011) Application of the entropy weight and TOPSIS method in safety evaluation of coal mines. Proced Eng 26:2085–2091CrossRefGoogle Scholar
  25. Masoumi I, Rashidinejad F (2011) Preference ranking of post‐mining land-use through LIMA framework. 9th international conference on clean technologies for the mining industry (Cleanmining), Santiago, ChileGoogle Scholar
  26. McHaina DM (2001) Environmental planning considerations for the decommissioning, closure and reclamation of a mine site. Int J Surf Min Reclam Environ 15(3):163–176CrossRefGoogle Scholar
  27. Meech JA, McPhie M, Clausen K, Simpson Y, Lang B, Campbell E, Johnstone S, Condon P (2006) Transformation of a derelict mine site into a sustainable community: the Britannia project. J Clean Prod 14:349–365CrossRefGoogle Scholar
  28. Miao Z, Marrs R (2000) Ecological restoration and land reclamation in open-cast mines in Shanxi Province China. J Environ Manag 59:205–215CrossRefGoogle Scholar
  29. Pavloudakis F, Galetakis M, Roumpos CH (2009) A spatial decision support system for the optimal environmental reclamation of open-pit coal mines in Greece. Int J Min Reclam Environ 23(4):291–303CrossRefGoogle Scholar
  30. Ramani RV, Sweigard RJ, Clar ML (1990) Reclamation planning. In: Kennedy BA (ed) Surface mining, 2nd edn. Society for mining, metallurgy, and Exploration, Inc, Littleton, pp 750–769Google Scholar
  31. Saaty TL (1980) The analytic hierarchy process. McGraw-Hill, New YorkGoogle Scholar
  32. Soltanmohammadi H, Osanloo M, Bazzazi AA (2008a) Deriving preference order of post-mining land-uses through MLSA framework: application of an outranking technique. Environ Geol 58:877–888CrossRefGoogle Scholar
  33. Soltanmohammadi H, Osanloo M, Rezaei B, Aghajani Bazzazi A (2008b) Achieving to some outranking relationships between post mining land uses through mined land suitability analysis. Int J Environ Sci Technol 5(4):535–546CrossRefGoogle Scholar
  34. Soltanmohammadi H, Osanloo M, Bazzazi AA (2010) An analytical approach with a reliable logic and a ranking policy for post-mining land-use determination. Land Use Policy 27:364–372CrossRefGoogle Scholar
  35. Sweigard RJ, Ramani RV (1988) Evaluation of postmining land use plans using fuzzy set analysis. Transactions of SME-AIME Annual Meeting, New Orleans, LA 282:1854–1859Google Scholar
  36. Torfi F, Farahani RZ, Rezapour S (2010) Fuzzy AHP to determine the relative weights of evaluation criteria and fuzzy TOPSIS to rank the alternatives. Appl Soft Comput J 10(2):520–528CrossRefGoogle Scholar
  37. Uberman R, Ostręga A (2005) Applying the analytic hierarchy process in the revitalization of post-mining areas field. ISAHP, HonoluluGoogle Scholar
  38. Vahidnia MH, Alesheikh AA, Alimohammadi A (2009) Hospital site selection using fuzzy AHP and its derivatives. J Environ Manag 90:3048–3056CrossRefGoogle Scholar
  39. Vaidya OS, Kumar S (2006) Analytic hierarchy process: an overview of applications. Eur J Oper Res 169:1–29CrossRefGoogle Scholar
  40. Wang TC, Chen YH (2007) Applying consistent fuzzy preference relations to partnership selection. Omega 35:384–388CrossRefGoogle Scholar
  41. Zavadskas EK, Antucheviciene J (2006) Development of an indicator model and ranking of sustainable revitalization alternatives of derelict property: a Lithuanian case study. Sustain Dev 14:287–299CrossRefGoogle Scholar
  42. Zhi-hong Z, Yi Y, Jing-nan S (2006) Entropy method for determination of weight of evaluating in fuzzy synthetic evaluation for water quality assessment indicators. J Environ Sci 18(5):1020–1023CrossRefGoogle Scholar

Copyright information

© Springer-Verlag Berlin Heidelberg 2013

Authors and Affiliations

  • Isa Masoumi
    • 1
    Email author
  • Saeed Naraghi
    • 1
  • Farshad Rashidi-nejad
    • 2
  • Shiba Masoumi
    • 3
  1. 1.Department of Mining Engineering, Science and Research BranchIslamic Azad UniversityTehranIran
  2. 2.School of Mining EngineeringUniversity of New South WalesSydneyAustralia
  3. 3.Department of Industrial Management, Babol BranchIslamic Azad UniversityMazandaranIran

Personalised recommendations