Project safety evaluation by a new soft computing approach-based last aggregation hesitant fuzzy complex proportional assessment in construction industry

Document Type : Article


1 Young Researchers and Elite Club, South Tehran Branch, Islamic Azad University, Tehran, Iran

2 Department of Industrial Engineering, Faculty of Engineering, Shahed University, Tehran, Iran

3 Faculty of Industrial and Mechanical Engineering, Qazvin Branch, Islamic Azad University, Qazvin, Iran

4 Laboratoire de Conception, Fabrication Commande, Arts et Métier Paris Tech, Centre de Metz, Metz, France


In recent years, the implementation of safety management has been increased in construction projects by institutions, and many companies have recognized environmental and social effects of injuries at project work systems. In this regard, a novel decision model is presented based on a new version of complex proportional assessment method with last aggregation under a hesitant fuzzy environment. The decision makers (DMs) assign their opinions by hesitant linguistic variables that are converted to the hesitant fuzzy elements. Also, the DMs’ judgments are aggregated in last step of decision making to decrease information loss. Since weights of the DMs or professional safety experts and evaluation criteria are not equal in practice, a new version of hesitant fuzzy compromise solution method is proposed to compute these weights. In addition, the criteria weights are determined based on proposed hesitant fuzzy entropy method. A real case study in developing countries about the safety of construction projects is considered to indicate the suitability and applicability of the proposed new hesitant fuzzy decision model with last aggregation approach. In addition, an illustrative example is prepared to show that the proposed approach is suitable and reliable in larger size safety problems


Main Subjects

1. Janic, M. An assessment of risk and safety in civil
aviation", Journal of Air Transport Management, 6(1),
pp. 43{50 (2000).
2. Odegard, S. Safety management in civil aviation: A
useful method for improved safety in medical care",
Safety Science Monitor, 4(1), pp. 1{12 (2000).
3. Malekly, H., Mousavi, S.M., and Hashemi, H. A
fuzzy integrated methodology for evaluating conceptual
bridge design", Expert Systems with Applications,
37(7), pp. 4910{4920 (2010).
4. Bailey, N. Risk perception and safety management
systems in the global maritime industry", Policy and
Practice in Health and Safety, 4(2), pp. 59{75 (2006).
5. Bhattacharya, S., Impact of the ISM Code on the
Management of Occupational Health and Safety in the
Maritime Industry, Cardi University (2009).
6. Horlick-Jones, T. Reasoning about safety management
policy in everyday terms: a pilot study in citizen
engagement for the UK railway industry", Journal of
Risk Research, 11(6), pp. 697{718 (2008).
7. Kudla, N. and Majumdar, A., Developing and Testing
Model of Data Quality for Safety Management
Information Systems: Exploratory Study in British
Railway Industry, in Transportation Research Board,
92nd Annual Meeting (2013).
8. Mousavi, S.M., Mirdamadi, S., Siadat, A., Dantan, J.,
and Tavakkoli-Moghaddam, R. An intuitionistic fuzzy
grey model for selection problems with an application
998 H. Gitinavard et al./Scientia Iranica, Transactions E: Industrial Engineering 27 (2020) 983{1000
to the inspection planning in manufacturing rms",
Engineering Applications of Arti cial Intelligence, 39,
pp. 157{167 (2015).
9. Vahdani, B., Mousavi, S.M., and Tavakkoli-
Moghaddam, R. Group decision making based on
novel fuzzy modi ed TOPSIS method", Applied
Mathematical Modelling, 35(9), pp. 4257{4269 (2011).
10. 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",
International Journal of Advanced Manufacturing
Technology, 73(5{8), pp. 687{697 (2014).
11. XIAO-ming, W. and LIU, X.-Y. Safety system management
and safety information management in major
transportation construction projects", Safety and Environmental
Engineering, 3, p. 015 (2011).
12. Guo, H., Li, H., and Li, V. VP-based safety management
in large-scale construction projects: A conceptual
framework", Automation in Construction, 34, pp.
16{24 (2013).
13. Mousavi, S.M., Tavakkoli-Moghaddam, R., Azaron,
A., Mojtahedi, S., and Hashemi, H. Risk assessment
for highway projects using jackknife technique", Expert
Systems with Applications, 38(5), pp. 5514{5524
14. Hashemi, H., Mousavi, S.M., and Mojtahedi, S.M.H.
Bootstrap technique for risk analysis with interval
numbers in bridge construction projects", Journal of
Construction Engineering and Management, 137(8),
pp. 600{608 (2011).
15. Vahdani, B., Mousavi, S.M., Hashemi, H.,
Mousakhani, M., and Tavakkoli-Moghaddam, R. A
new compromise solution method for fuzzy group
decision-making problems with an application to the
contractor selection", Engineering Applications of
Arti cial Intelligence, 26(2), pp. 779{788 (2013).
16. Schinas, O. Examining the use and application of
multi-criteria decision making techniques in safety
assessment", in International Symposium on Maritime
Safety, Security and Environmental Protection (2007).
17. Fazil, A., Rajic, A., Sanchez, J., and McEwen, S.
Choices, choices: the application of multi-criteria
decision analysis to a food safety decision-making
problem", Journal of Food Protection, 71(11), pp.
2323{2333 (2008).
18. Jozi, A.S. and Pouriyeh, A.A. Health-safety and environmental
risk assessment of power plants using multi
criteria decision making method", Chemical Industry
and Chemical Engineering Quarterly, 17(4), pp. 437{
449 (2011).
19. Mangalathu, S.G., Shanmugam, N.S., Sankaranarayanasamy,
K., Ramesh, T., and Muthukumar, K.
System safety in LPG red furnace - A multi criteria
decision making technique", Advances in Production
Engineering & Management, 7(2), pp. 123{134 (2012).
20. Zadeh, L.A. Fuzzy sets", Information and Control,
8(3), pp. 338{353 (1965).
21. Kahraman, C., Onar, S.C., and Oztaysi, B. Fuzzy
multicriteria decision-making: a literature review",
International Journal of Computational Intelligence
Systems, 8(4), pp. 637{666 (2015).
22. Bao, Q. Multi-criteria decision making techniques for
combining di erent sets of road safety performance
indicators into an overall index", Master's Thesis of
Transportation Science at Hasselt University (2010).
23. Mojtahedi, S.M.H., Mousavi, S.M., and Makui, A.
Project risk identi cation and assessment simultaneously
using multi-attribute group decision making
technique", Safety Science, 48(4), pp. 499{507 (2010).
24. Mousavi, S.M., Tavakkoli-Moghaddam, R., Hashemi,
H., and Mojtahedi, S.M.H. A novel approach based
on non-parametric resampling with interval analysis
for large engineering project risks", Safety Science,
49(10), pp. 1340{1348 (2011).
25. Khorasani, G., Mirmohammadi, F., Hassan Motamed,
M.F., Tatari, A., Verki, M.R.M., Khorasani, M., and
Fazelpour, S. Application of multi criteria decision
making tools in road safety performance indicators and
determine appropriate method with average concept",
International Journal of Innovative Technology and
Exploring Engineering (IJITEE), 3(5) (2013).
26. Skorupski, J. Multi-criteria group decision making
under uncertainty with application to air trac
safety", Expert Systems with Applications, 41(16), pp.
7406{7414 (2014).
27. Torra, V. and Narukawa, Y. On hesitant fuzzy sets
and decision", in Fuzzy Systems, FUZZ-IEEE 2009,
IEEE International Conference on (2009).
28. Torra, V. Hesitant fuzzy sets", International Journal
of Intelligent Systems, 25(6), pp. 529{539 (2010).
29. Farhadinia, B. A novel method of ranking hesitant
fuzzy values for multiple attribute decision-making
problems", International Journal of Intelligent Systems,
28(8), pp. 752{767 (2013).
30. Yu, D., Zhang, W., and Xu, Y. Group decision making
under hesitant fuzzy environment with application
to personnel evaluation", Knowledge-Based Systems,
52, pp. 1{10 (2013).
31. Wang, J.Q., Wang, D.D., Yu Zhang, H., and Chen,
X.H. Multi-criteria outranking approach with hesitant
fuzzy sets", OR Spectrum, 36(4), pp. 1001{1019
32. Zhang, Y., Wang, Y., and Wang, J. Objective attributes
weights determining based on Shannon information
entropy in hesitant fuzzy multiple attribute
decision making", Mathematical Problems in Engineering,
2014, pp. 30{36 (2014).
33. Rodrguez, R.M., Martnez, L., Torra, V., Xu, Z., and
Herrera, F. Hesitant fuzzy sets: state of the art and
future directions", International Journal of Intelligent
Systems, 29(6), pp. 495{524 (2014).
H. Gitinavard et al./Scientia Iranica, Transactions E: Industrial Engineering 27 (2020) 983{1000 999
34. Pei, Z. and Yi, L. A note on operations of hesitant
fuzzy sets", International Journal of Computational
Intelligence Systems, 8(2), pp. 226{239 (2015).
35. Yan, X. An approach to evaluating the risk of
marketing with hesitant fuzzy information", IJACT:
International Journal of Advancements in Computing
Technology, 4(9), pp. 122{128 (2012).
36. Yu, D., Wu, Y., and Zhou, W. Generalized hesitant
fuzzy Bonferroni mean and its application in multicriteria
group decision making", Journal of Information
and Computational Science, 9(2), pp. 267{274
37. Xu, Z. and Zhang, X. Hesitant fuzzy multi-attribute
decision making based on TOPSIS with incomplete
weight information", Knowledge-Based Systems, 52,
pp. 53{64 (2013).
38. Liu, H. and Rodrguez, R.M. A fuzzy envelope for
hesitant fuzzy linguistic term set and its application to
multicriteria decision making", Information Sciences,
258, pp. 220{238 (2014).
39. Liu, D.-N. Model for evaluating the electrical power
system safety with hesitant fuzzy linguistic information",
Journal of Intelligent & Fuzzy Systems, 29(2),
pp. 725{730 (2015).
40. Chen, N., Xu, Z., and Xia, M. Interval-valued hesitant
preference relations and their applications to group
decision making", Knowledge-Based Systems, 37, pp.
528{540 (2013).
41. Farhadinia, B. Information measures for hesitant
fuzzy sets and interval-valued hesitant fuzzy sets",
Information Sciences, 240, pp. 129{144 (2013).
42. Li, L.-G. and Peng, D.-H. Interval-valued hesitant
fuzzy Hamacher synergetic weighted aggregation operators
and their application to shale gas areas selection",
Mathematical Problems in Engineering, 2014,
pp. 1{25 (2014).
43. Zhang, X. and Xu, Z. Interval programming method
for hesitant fuzzy multi-attribute group decision making
with incomplete preference over alternatives",
Computers & Industrial Engineering, 75, pp. 217{229
44. Torra, V. and Narukawa, Y., Modeling Decisions: Aggregation
Operators and Information Fusion, Springer
45. Fan, Z.-P., Ma, J., and Zhang, Q. An approach
to multiple attribute decision making based on fuzzy
preference information on alternatives", Fuzzy Sets and
Systems, 131(1), pp. 101{106 (2002).
46. Wang, Y.-M. and Parkan, C. A general multiple attribute
decision-making approach for integrating subjective
preferences and objective information", Fuzzy
Sets and Systems, 157(10), pp. 1333{1345 (2006).
47. Chen, C.-F. and Lee, C.-L. Determining the attribute
weights of professional conference organizer selection:
an application of the fuzzy AHP approach", Tourism
Economics, 17(5), pp. 1129{1139 (2011).
48. Feng, X., Zuo, W., Wang, J., and Feng, L. TOPSIS
method for hesitant fuzzy multiple attribute decision
making", Journal of Intelligent and Fuzzy Systems,
26(5), pp. 2263{2269 (2014).
49. Atanassov, K.T. Intuitionistic fuzzy sets", Fuzzy Sets
and Systems, 20(1), pp. 87{96 (1986).
50. Atanassov, K.T. More on intuitionistic fuzzy sets",
Fuzzy Sets and Systems, 33(1), pp. 37{45 (1989).
51. Atanassov, K.T. Two theorems for intuitionistic fuzzy
sets", Fuzzy Sets and Systems, 110(2), pp. 267{269
52. Xia, M. and Xu, Z. Hesitant fuzzy information
aggregation in decision making", International Journal
of Approximate Reasoning, 52(3), pp. 395{407 (2011).
53. Liao, H., Xu, Z., and Xia, M. Multiplicative consistency
of hesitant fuzzy preference relation and its
application in group decision making", International
Journal of Information Technology & Decision Making,
13(1), pp. 47{76 (2014).
54. Gitinavard, H., Mousavi, S.M., and Vahdani, B.
Soft computing-based new interval-valued hesitant
fuzzy multi-criteria group assessment method with
last aggregation to industrial decision problems", Soft
Computing, 21(12), pp. 3247-3265 (2017).
55. Wei, G., Zhao, X., and Lin, R. Some hesitant
interval-valued fuzzy aggregation operators and their
applications to multiple attribute decision making",
Knowledge-Based Systems, 46, pp. 43{53 (2013).
56. Xu, Z. and Xia, M. Distance and similarity measures
for hesitant fuzzy sets", Information Sciences,
181(11), pp. 2128{2138 (2011).
57. Zhu, B., Xu, Z., and Xia, M. Hesitant fuzzy geometric
Bonferroni means", Information Sciences, 205, pp. 72{
85 (2012).
58. Zhang, Z., Wang, C., Tian, D., and Li, K. Induced
generalized hesitant fuzzy operators and their application
to multiple attribute group decision making",
Computers & Industrial Engineering, 67, pp. 116{138
59. Zhang, N. and Wei, G. Extension of VIKOR method
for decision making problem based on hesitant fuzzy
set", Applied Mathematical Modelling, 37(7), pp.
4938{4947 (2013).