Civil Engineering Reference
In-Depth Information
Table 6.9
Transformation of linguistic degree of optimism to
w
-index values
Degree of
optimism
w
-index
Ranking of alternatives
Conservative
0.1
A
3
(0.46)
>
A
5
(0.43)
>
A
4
(0.33)
>
A
1
(0.22)
>
A
2
(0.16)
Moderately
conservative
0.3
A
3
(0.57)
>
A
5
(0.53)
>
A
4
(0.48)
>
A
1
(0.36)
>
A
2
(0.34)
Normative
0.5
A
3
(0.67)
>
A
5
(0.63)
>
A
4
(0.63)
>
A
2
(0.53)
>
A
1
(0.50)
Moderately
optimistic
0.7
A
4
(0.78)
>
A
3
(0.77)
>
A
5
(0.74)
>
A
2
(0.72)
>
A
1
(0.64)
Optimistic
0.9
A
4
(0.93)
>
A
2
(0.90)
>
A
3
(0.87)
>
A
5
(0.84)
>
A
1
(0.79)
criterion operator plays an important role, if available information is not
enough to assign disjoint probabilities to payoffs.
One shortcoming of this method is that it considers only the minimum
and maximum values of each alternative, thus, important information may
be missed. To overcome this problem, Yager (1988) introduced a new family
of aggregation techniques called the ordered weighted averaging (OWA)
operators that consider the ordinal position of each criterion. The degree
of optimism (Equation (6.13)) in OWA operators are described as
orness
.
Tesfamariam
et al.
(2010) have proposed a linguistic transformation func-
tion to quantify
orness
values. Each
orness
values are used as a surrogate
measure of
w
-index (Table 6.9), the fi ve options are ranked, and results are
summarized in Table 6.9. It can be noted that, for
w
-index
0.10, 0.30, 0.50,
A
3
and
A
2
are the most and least desired retrofi t alternative, respectively. It
is interesting to note that, with increasing
w
-index values, rank reversals
occur; for example, for
w
-index
=
0.70, 0.90,
A
4
and
A
1
are the most and
least desired retrofi t option, respectively.
=
6.5
Conclusions
Exposure of civil infrastructure systems to multiple hazards necessitates the
need for a robust risk analysis tool. In this chapter, an overview of seismic
risk assessment and management framework is provided, and prevalent
challenges are highlighted. The risk analysis is subject to scarcity of data,
lack of knowledge, and subjectivity. Various mathematical techniques and
uncertainty quantifi cation techniques available in the literature that deal
with complex problem of decision making under various types of uncertain-
ties are discussed. Moreover, a quantifi able measure of acceptable risk is
discussed by focusing on different features of individual and societal risks.
Risk management is an integral part of overall seismic risk analyses that
are used to promote risk transfer (insurance) and/or prevention and mitiga-
tion. Under the prevention and mitigation, 'best' retrofi t alternative can be
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