References
1. Rassa, A.A. and Vaziri, M. Sustainable transport
indicators: denition and integration", International
Journal of Environmental Science & Technology, 2, pp.
83{96 (2005).
2. Awasthi, A., Chauhan, S.S., and Omrani, H. Application
of fuzzy TOPSIS in evaluating sustainable transportation
systems", Expert Systems with Applications,
38, pp. 12270{12280 (2011).
3. Shiau, T.A. Evaluating transport infrastructure decisions
under uncertainty", Transportation Planning and
Technology, 37, pp. 525{538 (2014).
4. Halouani, N., Chabchoub, H., and Martel, J.M.
PROMETHEE-MD-2T method for project selection",
European Journal of Operational Research, 195,
pp. 841{849 (2009).
5. Awasthi, A. and Chauhan, S.S. A hybrid approach
integrating Anity Diagram, AHP and fuzzy TOPSIS
for sustainable city logistics planning", Applied Mathematical
Modelling, 36, pp. 573{584 (2012).
6. Mandic, D., Jovanovic, P., and Bugarinovic, M. Twophase
model for multi-criteria project ranking: Serbian
railways case study", Transport Policy, 36, pp. 88{104
(2014).
7. Liu, K., Zhang, J., Yan, X., Liu, Y., Zhang, D.,
and Hu, W. Safety assessment for inland waterway
transportation with an extended fuzzy TOPSIS", Proceedings
of the Institution of Mechanical Engineers,
M. Aghamohagheghi et al./Scientia Iranica, Transactions E: Industrial Engineering 28 (2021) 892{911 909
Part O: Journal of Risk and Reliability, 230, pp. 323{
333 (2016).
8. Gul, M., Guneri, A.F., and Nasirli, S.M. A fuzzybased
model for risk assessment of routes in oil transportation",
International Journal of Environmental
Science and Technology, pp. 1{16 (2018).
9. Kundu, P., Kar, S., and Maiti, M. A fuzzy MCDM
method and an application to solid transportation
problem with mode preference", Soft Computing,
18(9), pp. 1853{1864 (2014).
10. Pamucar, D. and Cirovic, G. The selection of transport
and handling resources in logistics centers using
Multi-Attributive Border Approximation area Comparison
(MABAC)", Expert Systems with Applications,
42(6), pp. 3016{3028 (2015).
11. Essaadi, I., Grabot, B., and Fenies, P. Location of
global logistic hubs within Africa based on a fuzzy
multi-criteria approach", Computers & Industrial Engineering,
132, pp. 1{22 (2019).
12. Deng, X., Wei, G., Gao, H., and Wang, J. Models for
safety assessment of construction project with some
2-tuple linguistic Pythagorean fuzzy Bonferroni mean
operators", IEEE Access, 6, pp. 52105{52137 (2018).
13. Mohagheghi, V., Mousavi, S.M., and Vahdani, B.
Enhancing decision-making
exibility by introducing
a new last aggregation evaluating approach based on
multi-criteria group decision making and Pythagorean
fuzzy sets", Applied Soft Computing, 61, pp. 527{535
(2017).
14. Gitinavard, H., Mousavi, S.M., and Vahdani, B.
A new multi-criteria weighting and ranking model
for group decision-making analysis based on intervalvalued
hesitant fuzzy sets to selection problems",
Neural Computing and Applications, 27(6), pp. 1593{
1605 (2016).
15. Samanta, S. and Jana, D.K. A multi-item transportation
problem with mode of transportation preference
by MCDM method in interval type-2 fuzzy environment",
Neural Computing and Applications, 31(2), pp.
605{617 (2019).
16. Mohagheghi, V., Mousavi, S.M., Aghamohagheghi,
M., and Vahdani, B. A new approach of multi-criteria
analysis for the evaluation and selection of sustainable
transport investment projects under uncertainty: A
case study", International Journal of Computational
Intelligence Systems, 10(1), pp. 605{626 (2017).
17. Zhang, X. Multicriteria Pythagorean fuzzy decision
analysis: a hierarchical QUALIFLEX approach with
the closeness index-based ranking methods", Information
Sciences, 330, pp. 104{124 (2016).
18. Foroozesh, N., Tavakkoli-Moghaddam, R., Mousavi,
S.M., and Vahdani, B. A new comprehensive possibilistic
group decision approach for resilient supplier
selection with mean-variance-skewness-kurtosis and
asymmetric information under interval-valued fuzzy
uncertainty", Neural Computing and Applications,
31(11), pp. 6959-6979 (2019).
19. Ma, J., Fan, Z.P., and Huang, L.H. A subjective and
objective integrated approach to determine attribute
weights", European Journal of Operational Research,
112, pp. 397{404 (1999).
20. Mousavi, S.M., Vahdani, B., Tavakkoli-Moghaddam,
R., and Tajik, N. Soft computing based on a fuzzy
grey group compromise solution approach with an
application to the selection problem of material handling
equipment", International Journal of Computer
Integrated Manufacturing, 27(6), pp. 547{569 (2014).
21. Wang, Z.J. and Li, K.W. An interval-valued intuitionistic
fuzzy multiattribute group decision making framework
with incomplete preference over alternatives",
Expert Systems with Applications, 39, pp. 13509{13516
(2012).
22. Chen, T.Y.,Wang, H.P., and Lu, Y.Y. A multicriteria
group decision-making approach based on intervalvalued
intuitionistic fuzzy sets: A comparative perspective",
Expert Systems with Applications, 38, pp.
7647{7658 (2011).
23. Vahdani, B., Mousavi, S.M., Tavakkoli-Moghaddam,
R., Ghodratnama, A., and Mohammadi, M. Robot
selection by a multiple criteria complex proportional
assessment method under an interval-valued
fuzzy environment", The International Journal of Advanced
Manufacturing Technology, 73(5{8), pp. 687{
697 (2014).
24. Xu, Z. A deviation-based approach to intuitionistic
fuzzy multiple attribute group decision making",
Group Decision and Negotiation, 19, pp. 57{76 (2010).
25. Hung, W.L. and Yang, M.S. Fuzzy entropy on intuitionistic
fuzzy sets", International Journal of Intelligent
Systems, 21, pp. 443{451 (2006).
26. Vlachos, I.K. and Sergiadis, G.D. Intuitionistic fuzzy
information-applications to pattern recognition", Pattern
Recognition Letters, 28, pp. 197{206 (2007).
27. Yue, Z. A method for group decision-making based
on determining weights of decision makers using TOPSIS",
Applied Mathematical Modelling, 35, pp. 1926{
1936 (2011).
28. Qi, X., Liang, C., and Zhang, J. Generalized crossentropy
based group decision making with unknown
expert and attribute weights under interval-valued
intuitionistic fuzzy environment", Computers & Industrial
Engineering, 79, pp. 52{64 (2015).
29. Opricovic, S. Multicriteria optimization of civil engineering
systems", Faculty of Civil Engineering, Belgrade,
2, pp. 5{21 (1998).
30. Peng, X. and Yang, Y. Fundamental properties of
interval-valued pythagorean fuzzy aggregation operators",
International Journal of Intelligent Systems, 31,
pp. 444{487 (2015).
31. Garg, H. A novel accuracy function under intervalvalued
Pythagorean fuzzy environment for solving
multicriteria decision making problem", Journal of
Intelligent & Fuzzy Systems, 31, pp. 1{12 (2016).
910 M. Aghamohagheghi et al./Scientia Iranica, Transactions E: Industrial Engineering 28 (2021) 892{911
32. Liang, W., Zhang, X., and Liu, M. The maximizing
deviation method based on interval-valued
pythagorean fuzzy weighted aggregating operator for
multiple criteria group decision analysis", Discrete
Dynamics in Nature and Society, 2015, Article ID
746572, pp. 1-15 (2015).
33. Szmidt, E. and Kacprzyk, J. Entropy for intuitionistic
fuzzy sets", Fuzzy Sets and Systems, 118, pp. 467{477
(2001).
34. Szmidt, E., Kacprzyk, J., and Bujnowski, P. How
to measure the amount of knowledge conveyed by
Atanassov's intuitionistic fuzzy sets", Information Sciences,
257, pp. 276{285 (2014).
35. Kim, S.H. and Ahn, B.S. Interactive group decision
making procedure under incomplete information", European
Journal of Operational Research, 116, pp. 498{
507 (1999).
36. Salling, K.B. and Pryn, M.R. Sustainable transport
project evaluation and decision support: indicators
and planning criteria for sustainable development",
International Journal of Sustainable Development &
World Ecology, 22, pp. 346{357 (2015).
37. Veron-Okamoto, A. and Sakamoto, K., Toward a Sustainability
Appraisal Framework for Transport, ADB
Sustainable Development Working Paper Series, Asian
Development Bank, Manila, Philippines (2014).
38. Ashtiani, B., Haghighirad, F., Makui, A., and Ali
Montazer, G. Extension of fuzzy TOPSIS method
based on interval-valued fuzzy sets", Applied Soft
Computing, 9(2), pp. 457{461 (2009).
39. Gitinavard, H., Mousavi, S.M., and Vahdani, B. Soft
computing based on hierarchical evaluation approach
and criteria interdependencies for energy decisionmaking
problems: A case study", Energy, 118, pp.
556{577 (2017).
40. Mousavi, M., Gitinavard, H., and Mousavi, S.M. A
soft computing based-modied ELECTRE model for
renewable energy policy selection with unknown information",
Renewable and Sustainable Energy Reviews,
68(1), pp. 774{787 (2017).
41. Vahdani, B., Salimi, M., and Mousavi, S.M. A new
compromise solution model based on Dantzig-wolf decomposition
for solving belief multi-objective nonlinear
programming problems with block angular structure",
International Journal of Information Technology &
Decision Making, 16(2), pp. 333{387 (2017).
42. Dorfeshan, Y., Mousavi, S.M., Mohagheghi, V., and
Vahdani, B. Selecting project-critical path by a new
interval type-2 fuzzy decision methodology based on
MULTIMOORA, MOOSRA and TPOP methods",
Computers & Industrial Engineering, 120, pp. 160{
178 (2018).
43. Mohagheghi, V., Mousavi, S.M., Vahdani, B., and
Siadat, A. A mathematical modeling approach for
high and new technology-project portfolio selection
under uncertain environments", Journal of Intelligent
and Fuzzy Systems, 32, pp. 4069{4079 (2017).
44. Wang, L.,Wang, H., Xu, Z., and Ren, Z. The intervalvalued
hesitant Pythagorean fuzzy set and its applications
with extended TOPSIS and Choquet integralbased
method", International Journal of Intelligent
Systems, 34(6), pp. 1063{1085 (2019).