A multi-criteria decision making approach for priority areas selection in membrane industry for investment promotion: a case study in Iran Marketplace

Document Type : Research Paper


1 Technology Development Institute (ACECR), Sharif university branch, Industrial Engineering Department

2 University of Science & Culture, Faculty of Basic Sciences and Advanced Technologies in biology


Membrane technologies for the separation of mixtures have gained an extensive worldwide attraction in the modern industrialized world. They have many industrial and medical applications such as water desalination, wastewater reclamation, gas separation, food and medical applications. However, even though all these applications have their own efficiency and market, the selection of priority applications is very challenging for most developing countries. On the other hand, selecting the optimal priority applications among many alternatives is a multi-criteria decision-making (MCDM) problem. This paper develops an evaluation model based on the AHP and TOPSIS methods for evaluating and ranking membrane applications effectively. The AHP is used to analyze the structure of the selection problem and to determine the weights of the evaluating criteria. It is also used for evaluating the decision-making team members to determine the relative importance of each one of them. A modified technique is proposed to improve the consistency of judgment matrices; then Individual judgments are aggregated by using the weighted geometric mean to obtain the weights of criteria. The modified technique increases the accuracy of decisionmaking process and saves time to obtain consistent judgment matrices. Finally, the TOPSIS method is employed to calculate the final ranking of the membrane applications. For evaluating the performance and reliability of the proposed model, it is applied in a real case in IRAN.


Adhikari, S., Fernando, S. (2006).Hydrogen membrane separation techniques. Industrial
Engineering and Chemical Research, 45, 875-881.
Amiri, P.M. (2010).Project selection for oil-fields development by using the AHP and fuzzy
TOPSIS methods.Expert Systems with Applications, 37, 6218–6224.
Arnal, J.M., Leon M.C., Lora J., Gozalvez J.M., Santafe A., Sanz D., &Tena J.
(2008).Ultrafiltration as a pre-treatment of other membranetechnologies in the reuse of textile
wastewaters.Desalination, 221, 405-412.
Baker, R.W. (2004).Membrane technology and applications.John Wiley and Sons, 2nd Edition.
Behling,N. H. (2013).Fuel Cells, Current Technology Challenges and Future Research
Needs.Chapter 7 – History of Proton Exchange Membrane Fuel Cells and Direct Methanol Fuel
Cells, Pages 423–600.
Breslau B.R., Larsen P.H., Milnes B.A.,& Waugh S.L. (1988).The Application of Ultra filtration
Technology in the Food Processing Industry.The Sixth Annual Membrane Technology/Planning
Conference, Cambridge.
Brunelli, M.,Fedrizzi, M. (2015).Boundary properties of the inconsistency of pairwise
comparisons in group decisions. European Journal of Operational Research, 240, 765–773.
Buyukozkan, G., Feyzioglu, O., &Nobel E. (2008).Selection of the strategic alliance partner in
logistics value chain.International Journal of Production Economics, 113, 148-158.
Chamodrakas, I., Alexopoulou, N., &Martakos, D. (2009). Customer evaluation for order
acceptance using a novel class of fuzzy methods based on TOPSIS.Expert Systems with
Applications, 36, 7409–7415.
Chan, F.T.S., Kumar, N. (2007). Global supplier development considering risk factors using
fuzzy extended AHP-based approach. Omega, 35, 417-431.
Chen, S.J., Hwang, C.L. (1992). Fuzzy multiple attribute decision making: Methods and
applications.Springer, Berlin.
Cheng, C.H., Yang, K.L., & Hwang C.L. (1999).Evaluating attack helicopters by AHP based on
linguistic variable weighs.European Journal of Operational Research, 116: 423–435.
Chen, C.T. (2000).Extensions of the TOPSIS for group decision-making under fuzzy
environment.Fuzzy Sets and Systems, 114, 1–9.
Chu, T.C. (2002).Selecting plant location via a fuzzy TOPSIS approach.International Journal of
Advanced Manufacturing Technology, 20, 859–864.
Chu, T. C., Lin, Y. C. (2002).Improved extensions of the TOPSIS for group decision making
under fuzzy environment.Journal of Information and Optimization Sciences, 23, 273–286.
Dagdeviren, M., Yüksel, I. (2008).Developing a fuzzy analytic hierarchy process (AHP) model
for behavior-based safety management.Information Science, 178, 1717–1733.
Dahl, G. (2005).A method for approximating symmetrically reciprocal matrices by transitive
matrices.Linear Algebra and Its Applications, 403, 207-215.
Dagdeviren, M., Yavuz, S., &Kılınç, N. (2009).Weapon selection using the AHP and TOPSIS
methods under fuzzy environment.Expert Systems with Applications, 36, 8143–8151.
Fane,A.G. , Tang,C.Y. , & Wang, R. (2011).Treatise on Water Science,Volume 4: Water-Quality
Engineering. 4.11 – Membrane Technology for Water: Microfiltration, Ultra filtration, Nan
filtration, and Reverse OsmosisPages 301–335.
Fifeld, C.W., Leahy, T.J. (1983). Sterilization filtration, In: Disinfection, Sterilization and
Preservation, ed. Block S.S., Lea and Febiger, Philadelphia.
Genets, C., Zhung, S. (1996). A graphical analysis of ratio-scaled paired comparison data.
Management Science, 42, 335-349.
Gumus, A.T. (2008). Evaluation of hazardous waste transportation firms by using a two step
fuzzy-AHP and TOPSIS methodology.Expert Systems with Applications, 36, 4067-4074.
Gupta, V.K., Ali, I. (2013).Environmental Water, Advances in Treatment, Remediation and
Recycling, Chapter 5 – Water Treatment by Membrane Filtration Techniques, Pages: 135–154.
Harker, P.T. (1987). Derivatives of the Perron root of a positive reciprocal matrix: with
application to the analytic hierarchy process.Applied Mathematics and Computation, 22, 217-
Henis, J.M.S., Tripodi, M.K. (1980). A novel approach to gas separation using compositehollow
fiber membranes.Separation Science & Technology, 15, 1059-1076.
Hartman, A. (1981).Reaching consensus using the Delphi technique, Educational Leadership, 38,
Hwang, C.L., Yoon, K. (1981). Multiple attributes decision making methods and applications.
Springer, Berlin.
Jahanshahloo, G.R., Lotfi, F.H.,&Izadikhah M. (2006).Extension of the TOPSIS method for
decision-making problems with fuzzy data.Applied Mathematics and Computation, 181(2), 1544-
Kilincci, O., Onal, S.A. (2011).Fuzzy AHP approach for supplier selection in a washing machine
company.Expert Systems with Applications, 38, 9656–9664.
Kolf, W.J., Berk, H.T. (1944). The artificial kidney: A dialyzer with great
area.ActaMedicaScandinavica, 117, 121-127.
Kulak, O.,Kahraman, C. (2005).Fuzzy multi-attribute selection among transportation companies
using axiomatic design and analytic hierarchy process. Information Sciences, 170, 191–210.
Lipnizki, F. (2010).Comprehensive Membrane Science and Engineering, Volume 4: Membrane
Contactors and Integrated Membrane Operations, 4.06 – Basic Aspects and Applications of
Membrane Processes in Agro-Food and Bulk Biotech Industries, Pages 165–194.
Loeb, S., Sourirajan, S. (1963).Sea water demineralization by means of an osmoticmembrane, in
Saline Water Conversion–II, Advances in Chemistry Series Number 28,American Chemical
Society, Washington, DC, 117-132.
Madaeni, S.S. (1999).The application of membrane technology for water disinfection.Water
Research, 33, 301-308.
McKeen,L. W. (2012).Permeability Properties of Plastics and Elastomers (Third Edition), Pages:
Miller, G.A. (1956). The magical number seven plus or minus two: some limitations on our
capacity for processing information, Psychological Review, 63: 81-97.
Vincke, P. (1992).Multi-criteria Decision-aid, Wiley.
Rahmani, M., Navidi H. (2009).A new approach to improve inconsistency in the Analytical
Hierarchy Process.Application and Applied Mathematics: An International Journal, 4(1), 40-51.
Reis, R.V., Zydney, A. (2007). Bioprocess membrane technology.Journal of Membrane Science,
297, 16-50.
Robeson,L.M. (2012). Polymer Science: A Comprehensive Reference.Volume 8: Polymers for
Advanced Functional Materials 8.13 – Pages 325–347.
Saaty, T.L. (1980). The Analytic Hierarchy Process.McGraw–Hill, NY.
Saaty, T.L. (1990).Multicriteria decision-making: The Analytic Hierarchy Process.RWS PWS,
Saaty, T.L. (2003). Decision making with the AHP: why is the principal eigenvector
necessary.European journal of operation research, 145: 85-91.
Saufi, S.M., Ismail, A.F. (2004). Fabrication of carbon membranes for gas separation: A review.
Carbon, 41, 241-259.
Shyur, H. J., Shih, H. S. (2006).A hybrid MCDM model for strategic vendor
selection.Mathematical and Computer Modeling, 44, 749–761.
Spillman,R. (1995).Membrane Science and TechnologyVolume 2, Membrane Separations
Technology, Principles and Applications. Chapter 13 Economics of gas separation membrane
processes, Pages 589–667.
Stamatialis, D. F., Papenburg,B. J. , Gironés, M.,Saiful, S., BettahalliaSrivatsa, N.M.
&Wessling,M. (2008). Medical applications of membranes: Drug delivery, artificial organs and
tissue engineering. Journal of Membrane Science, Volume 308, Issues 1–2, Pages 1–34.
Wang, T. C., Chang, T. H. (2007).Application of TOPSIS in evaluating initial trainingaircraft
under a fuzzy environment.Expert Systems with Applications, 33, 870–880.
Wang, J., Liu, S. Y., & Zhang, J. (2005).An extension of TOPSIS for fuzzy MCDM based on
vague set theory.Journal of Systems Science and Systems Engineering, 14, 73–84.
Wang, Y. M., Elhag, T. M. S. (2006). Fuzzy TOPSIS method based on alpha level sets with an
application to bridge risk assessment. Expert Systems with Applications, 31, 309–319.
Williams, M.E., Bhattacharyya, D., Ray, R.J., &McCray S.B. (1992). Selected applications of
Reverse Osmosis, in Membrane Handbook, Ho W.S.W., and Sirkar K.K. (eds), VanNostrand
Reinhold, New York, 312-354.