1 Department of Environment, Islamic Azad University, Parand Branch, Parand, Iran

2 Department of Mathematics, Qazvin Branch, Islamic Azad University, Qazvin, Iran

3 Central Tehran Branch, Islamic Azad University, Tehran, Iran

4 Aerospace Research Institute, Ministry of Science, Research and Technology, Mahestan Street, Tehran, Iran


The proper management of oily sludge from petroleum products storage tanks is necessary because inappropriate methods for dredging of tanks may result in high costs and increased environmental pollution. The purpose of the current study is to rank the strategies outlined by strengths, weaknesses, opportunities and threats analysis using data envelopment analysis model, which provides enriched insights into management of waste from dredging of tanks. As a result, with the use of strengths, weaknesses, opportunities and threat analysis, the strengths, weaknesses, opportunities, and threats were determined and some management strategies for oily sludge were obtained. Afterward, fuzzy data envelopment analysis was used to prioritize the strategies. Using experts' opinions, strategies can be ranked and prioritized by solving the data envelopment analysis model according to the acquired optimal solutions. An important point in this method is that experts' opinions are also incorporated into the analysis. Sixteen strategies are presented based on the strengths, weaknesses, opportunities and threat analysis and prioritized based on fuzzy data envelopment analysis. Strategies number 14 and 10, based on weakness-opportunities and strengths-threats respectively are of first priorities. Therefore, the strategies such as development of executive instructions and guidelines, elaboration of duties of managers regarding waste management and construction of a suitable and centralized site for storing oily sludge according to environmental requirements could be strategically useful for the management of oily sludge from storage tanks.

Graphical Abstract


  • Data envelopment analysis model was used to rank the strategies developed by strengths, weaknesses, opportunities and threat analysis
  • Fuzzy data envelopment analysis model was used to prioritize the strategies
  • The strategies were prioritized based on the data envelopment analysis model using fuzzy data, which could be useful for the management of oily sludge from dredging of tanks at the strategic level.


Main Subjects

Adetutu, E.M.; Bird, C.; Kadali, K.K.; Bueti, A.; Shahsavari, E.; Taha, M.; Patil, S.; Sheppard, P.J.; Makadia, T.; Simons, K.L.; Ball, A.S., (2015). Exploiting the intrinsic hydrocarbon-degrading microbial capacities in oil tank bottom sludge and waste soil for sludge bioremediation. Int. J. Environ. Sci. Technol., 12(4): 1427-1436 (10 pages).

Al-Futaisi, A.; Jamrah, A.; Yaghi, B.; Taha, R., (2007). Assessment of alternative management techniques of tank bottom petroleum sludge in Oman. J. Hazard. Mater., 141(3): 557-564 (8 pages).

Andersen, P.; Petersen, N.C., (1993). A procedure for ranking efficient units in data envelopment analysis. Manage. Sci., 39(10):1261-1264 (4 pages).

Asia, I.O.; Enweani, I.B.; Eguavoen, I.O., (2006). Characterization and treatment of sludge from the petroleum industry. Afr. J. Biotechnol., 5(5): 461-466 (6 pages).

Borgheipour, H.; Lotfi, F.H.; Moghaddas, Z., (2017). Implementing energy efficiency for target setting in the sugar industry of Iran. Int. J. Environ. Sci. Technol., 14(8):1697-1712 (16 pages).

Cooper, W.W.; Li, S.; Seiford, L.M.; Tone, K.; Thrall, R.M.; Zhu, J., (2001). Sensitivity and stability analysis in DEA: some recent developments. J. Prod. Anal., 15(3): 217-246 (30 pages).

Charnes, A.; Cooper, W.W.; Rhodes, E., (1978). Measuring the efficiency of decision making units. Eur. J. Oper. Res., 2(6): 429-444 (16 pages).

Dubois, D.J., (1980). Fuzzy sets and systems: theory and applications (Vol. 144). Academic Press.

Fang, H.H.; Lee, H.S.; Hwang, S.N.; Chung, C.C., (2013). A slacks-based measure of super-efficiency in data envelopment analysis: An alternative approach. Omega, 41(4): 731-734 (4 pages).

Färe, R.; Grosskopf, S., (2010). Directional distance functions and slacks-based measures of efficiency. Euro. J. Ope. Res., 200(1): 320-322 (3 pages).

Ghorbani, M.; Bahrami, M.; Arabzad, S.M., (2012). An integrated model for supplier selection and order allocation; using Shannon entropy, SWOT and linear programming. Proc-Soc. Behav.  Sci,, 41: 521-527 (7 pages).

Heath, G.M.; Heath, R.A.; Dundr, Z., (2004). Paraffinic sludge reduction in crude oil storage tanks through the use of shearing and resuspension.  Acta Morphol. Neerl.-Scand., 9: 184-188 (5 pages).

Ho, W., (2008). Integrated analytic hierarchy process and its applications–A literature review. Eur. J. Oper. Res., 186(1): 211-228 (18 pages).

Hosseinzadeh, A.A.; Hosseinzadeh Lotfi, F.; Moghaddas, Z., (2016). Fuzzy efficiency: Multiplier and enveloping CCR‎ models‎. Int. J. Indus. Math., 8(1): 1-8 (8 pages).

Hu, G.; Li, J.; Zeng, G., (2013). Recent development in the treatment of oily sludge from petroleum industry: a review. J. Hazard. Mater., 261: 470-490 (21 pages).

Islam, B., (2015). Petroleum sludge, its treatment and disposal: A review. Int. J. Chem. Sci., 13(4):1584–1602 (19 pages).

Jafarinejad, S., (2016). Petroleum waste treatment and pollution control. 1st. Ed., Elsevier Publisher.

Jahantigh, M.; Hosseinzadeh, L.F.; Moghaddas, Z., (2013). Ranking of DMUs by using TOPSIS and        diferent ranking models in DEA. Int. J. Ind. Math., 5(3): 217-225 (9 pages).

Jing, G.; Chen, T.; Luan, M., (2016). Studying oily sludge treatment by thermo chemistry. Arabian J. Chem., 9: S457-S460 (4 pages).

Klir, G.J.;Yuan, B., (1995). Fuzzy sets and fuzzy logic. (Vol. 4). New Jersey: Prentice hall.

Kriipsalu, M.; Marques, M.; Maastik, A., (2008). Characterization of oily sludge from a wastewater treatment plant flocculation-flotation unit in a petroleum refinery and its treatment implications. J. Mater. Cycles Waste Manage., 10(1): 79-86 (8 pages).

Liu, W.B.; Zhang, D.Q.;  Meng, W.; Li, X.X.; Xu, F., (2011). A study of DEA models without explicit inputs. Omega. 39(5): 472-480 (9 pages).

Lovell, C.A.K.; Pastor, J.T., (1999).  Radial DEA models without inputs or without outputs. Euro. J. Ope. Res., 118 (1): 46-51 (6 pages).

Lozano, M.; Vallés, J., (2007). An analysis of the implementation of an environmental management system in a local public administration. J. Environ. Manage., 82(4): 495-511 (17 pages).

Moogouei, R., (2014). A SWOT analysis of aquaculture development in rural areas of Iran, an application to Rainbow trout (Oncorhynchus mykiss). Int. J. Aquat. Biol., 2(1): 36-42 (7 pages).

NIOPDC, (2017). National Iranian Oil Products Distribution Company.

Nouri, J.; Lotfi, F.H.; Borgheipour, H.; Atabi, F.; Sadeghzadeh, S.M.; Moghaddas, Z., (2013). An analysis of the implementation of energy efficiency measures in the vegetable oil industry of Iran: a data envelopment analysis approach. J. Cleaner Prod., 52: 84-93 (10 pages).

Philemon, Z.B.O.; Benoît, N.M., (2013). Treatment of conditioned oily sludge from Cameroon petroleum refinery by centrifugation. Int. J. Environ. Sci., 3(5): 1373-1382 (10 pages).

Saati, S.M.; Memariani, A.; Jahanshahloo, G.R., (2002). Efficiency analysis and ranking of DMUs with fuzzy data. Fuzzy Opt. Decis. Mak, 1(3): 255-267 (13 pages).

Shahba, S.; Arjmandi, R.; Monavari, M.; Ghodusi, J., (2017). Application of multi-attribute decision-making methods in SWOT analysis of mine waste management: Case study: Sirjan's Golgohar iron mine, Iran Resour. Policy, 51: 67-76 (10 pages).

Tone, K., (2001). A slacks-based measure of efficiency in data envelopment analysis. Eur. J. Ope. Res., 130(3): 498-509 (12 pages).

Zade, l.A., (1965). Fuzzy Sets. Inf. control 8: 338-353 (16 pages).

Zare, K.; Mehri-Tekmeh, J.; Karimi, S., (2015). A SWOT framework for analyzing the electricity supply chain using an integrated AHP methodology combined with fuzzy-Topsis. Int. Strategy Manage. Rev., 3(1): 66-80 (15 pages).

Zimmermann, A., (1986). Fuzzy sets theory and its application. Kluwer, Dorrecht.



Borgheipour, H.; Moghaddas, Z.; Abbasi, M.; Abbaszadeh Tehrani, N., (2018). Fuzzy DEA in SWOT analysis of oily sludge management. Global J. Environ. Sci. Manage., 4(2): 183-194 (12 pages).

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