This study presents a supporting tool for the decision-making process based on the Analytic Hierarchy Process (AHP) in construction management. This tool is built in Visual Basic for Applications (VBA) language and run in Microsoft Excel spreadsheet software.
Trang 1ISSN 1859-1531 - THE UNIVERSITY OF DANANG, JOURNAL OF SCIENCE AND TECHNOLOGY, NO 6(115).2017 55
STUDYING THE APPLICATION OF A MULTIPLE-CRITERIA DECISION-MAKING METHOD IN CONSTRUCTION MANAGEMENT BASED ON VISUAL
BASIC PROGRAMMING LANGUAGE Pham Anh Duc, Truong Ngoc Son, Vo Van Thuan, Ho Thi Ngoc Nhung, Doan Thi Thu Oanh
University of Science and Technology - The University of Danang;
paduc@dut.udn.vn; tnson@dut.udn.vn; vanthuan0609@gmail.com
Abstract - Making decision under multiple criteria is a fertile
research area with lots of scope for real-life applications However,
the decision-making process is limited on subjective assessments
and it has not been balanced between costs and benefits This
study presents a supporting tool for the decision-making process
based on the Analytic Hierarchy Process (AHP) in construction
management This tool is built in Visual Basic for Applications
(VBA) language and run in Microsoft Excel spreadsheet software
It will provide a convenient, reliable and faster way for the user to
make a decision and get the final result of the decision by showing
the best alternative based on the most important criteria This tool
is time-saving and reduces errors in decision-making process in
many fields, especially in construction management
Key words - decision-making; multiple-criteria; AHP; construction
management; VBA
1 Introduction
Decision-making is an important part of most human
activities, whether we are performing daily activities,
professional or political work Some decisions may be
relatively simple, especially if the consequences of a bad
decision are small, while others can be very complex and
have significant effects Real-life decision problems will,
in general, involve several conflicting points of view
(criteria) that should be taken into account conjointly, in
order to achieve a reasonable solution [1]
In the construction management field, making decisions
based on multiple criteria is an integral part including
selections of contractors, suppliers, consultants, and so forth
The decision-making process may cause conflicts among
criteria For example, making decision based only on the
lowest cost or the largest profit may lead to an unrealistic
decision due to lack of quantitative factors [2] Therefore, a
decision making process needs comprehensive
consideration for multiple criteria to improve the accuracy
and figure out optimal choices To tackle this issue, in recent
years, various researchers have applied the theories
ofmultiple-criteriaapproach to assess the comprehensive
impacts of the factors on the decision-making process The
Analytic Hierarchy Process (AHP) is one of the methods
supporting the decision-making process that is utilized in
various fields such as science, economics, healthcare,
education, and especially in the construction industry
The accuracy in making decisions is increasingly
required and technologies have been developing towards
the trend of automation Therefore, the researchers have
decided to develop a tool supporting multiple-criteria
decision-making activities This tool adopted the Visual
Basic for Applications (VBA) programming language
which was integrated in Excel spreadsheet software VBA
is a programming language which is developed for office
applications and VBA has been supporting Excel software with high customization capability beyond ordinary spreadsheet limits as well as the capability of solving complex problems and higher automation This tool can help users make decisions quickly and relevantly based on logical calculations Besides, this study provides readers with comprehensive understanding of the AHP method and its applications in the aspects of life
2 Theoretical background
Analytical Hierarchical Process (AHP) is one of the multi -criteria decision making tools that have been used widely in assisting people and organization in their decision making process The AHP was developed by Saaty (1980)
to deal with multiple-criteria problems [3] It is designed to solve complex multi-criteria decision problems AHP requires the decision maker to provide judgements about the relative importance of each criterion and then to specify a preference for each decision alternative using each criterion AHP allows better, easier and more efficient identification
of selection criteria, their weighting and analysis AHP allows a logical mixture of data, which could be quantitative, qualitative, experience, insight, and intuition in its algorithmic framework It enables decision makers to find the weight of each criterion [4] Subsequently, Saaty and Vargas (1994) introduced the applications of AHP to solve economic, political, and social problems as well as those related to technical designs [5]
AHP’s applications for selecting suppliers:
Al-Harbi (2001) introduced the application of AHP as
a potential method for selecting the optimal contractor in project management [6] He constructed a hierarchical structure for the prequalified criteria and the contractors wishing to take part in the prequalifying stage Besides, Tam and Tummala (2001) applied the AHP for selecting telecom system providers [7], which was a complex and multiple-criteria process
AHP’s applications for selecting construction site:
Korpela and Tuominen (1996) presented an integrated approach in selecting warehouse’s location, in which both quantitative and qualitative factors are considered [8] Besides, Badri (1999) utilized the AHP for site selection [9] He confirmed that the AHP could help the staff in making plan for building strategies
AHP’s applicationsin forecasting:
Korpela and Tuominen (1997) used the AHP to forecast the inventory demand [10] Some of the AHP’s applications in different fields are shown in Table 1
Trang 256 Pham Anh Duc, Truong Ngoc Son, Vo Van Thuan, Ho Thi Ngoc Nhung, Doan Thi Thu Oanh Recently, the AHP method has been studied in Viet
Nam Dang The Ba and Pham Thi Minh Hanh (2013)
applied decision support system in water resource
management for the Dakmi 4 dam [11]
Table 1 Applications of AHP in making decisions
lier Dweiri, F., et al.,,
(2016) [1]
Supplier selection in automobile industry
h G Büyüközkan,
and G Çifçi,
(2012) [12]
A combined fuzzy AHP and fuzzy TOPSIS based strategic analysis of electronic service
quality in healthcare industry
n J.-F Chen, H.-N
Hsieh, and Q H
Do (2015) [13]
Evaluating teaching performance based on fuzzy AHP
The works mentioned previously show that AHP is a
very useful and beneficial method as an aiding tool in
decision making process However, there are very few tools
where AHP process is supported automatically This study
builds a tool based on multiple-criteria decision-making
method with fast calculating process and easily applied in
order to tackle issues in management, learning, and research,
compared to previous studies This study also uses the
proposed tool for selecting appropriate type of bridge in
construction management Thereby, the high applicability of
the proposed tool in the construction industry is obvious
3 The proposed method
3.1 Multiple-criteria decision analysis
Multiple-criteria decision making (MCDM) is a sub-field
of operations research or management science and has
attracted an increasing attention of researchers for decades A
considerable amount of literature has been published on
various MCDM methods and their applications [14] The
general objective of MCDM is to assist the decision-maker
(DM) in selecting the 'best' alternative from the number of
feasible choice-alternatives under the presence of multiple
choice criteria and diverse criterion priorities MCDM
method manages the complexity of criteria by converting
from the qualitative assessment into scoring In recent years,
researchers have improved and developed the MCDM
method into various methods which was divided into 4
families [15]: the Multi-attribute utility theory– MAUT,the
Multi-criteria decision analysis methods– ELECTRE, the
Preference Ranking Organization Method for Enrichment of
Evaluations - PROMETHEE, and the AHP The advance of
the AHP method is not only capable of controlling the
consistency of the judgments from experts but also the
evaluation process of this method is conducted independently
from any arising issues and experts, ensuring the objectivity
of assessment The AHP method has proven its efficiency
through the successful application in many fields
3.2 AHP method
AHP is a method of multi-criteria decision developed
by Saaty (1980) [3]
The AHP is based on three principles:
a Analyzing data: First, AHP analyzes a
multiple-criteria problem based ona hierarchical structure The hierarchical structure diagrams start with the target analyzed through the major criteria and the componential criteria, and the final rank usually includes relevant options
b Comparing elements in the corresponding level:
Based on their own knowledge and experience, the interviewees will express their opinions on each pair of elements by answering questions To assess the level of importance or superiority of this element compared to the other elements, the scale (Table 2) is made with the values from 1 to 9 (pair-wise comparisons)
Table 2 Pair-wise comparison scale for AHP preferences [3]
rating
1 Equally preferred 1
2 Moderately preferred 3
3 Strongly preferred 5
4 Very strongly preferred 7
5 Extremely preferred 9
6 The average values 2,4,6,8
The final result is a set of pair-wise comparison
matrices (size n x n) for each of the lower levels with one
matrix for each element in the level immediately above (Table 3) If the element A is more important than element
B and rated at 9, B will be rated as less important than A
with a value of 1/9
Table 3 The judgment matrix
c Synthesis of priorities: The method aggregate the
pair-wise comparison data to have common values of priority Saaty used the method of least squares to obtain weights from the pair-wise comparison Summation method is used
to solve the maximum eigenvalue of the matrix:
- Calculating the total of each column in the matrix ∑aij (Table 4)
- Synthesizing the pair-wise comparison matrix is performed by dividing each element of the matrix by its column total Wij= aij/∑aij, The priority vector can be obtained by finding the row averages (Table 5)
Table 4 Comparison matrix of factors
Trang 3ISSN 1859-1531 - THE UNIVERSITY OF DANANG, JOURNAL OF SCIENCE AND TECHNOLOGY, NO 6(115).2017 57
Table 5 Matrix of consistent index(w)
- Checking the consistency: Saaty (1990) used a
consistency ratio CR [16] to check the consistency of the
priority elements, if consistency ratio CR0.1 then the
assessment is fairly consistent, on the contrary, the
assessment is inaccurate
Consistency index (CI) is determined as follows:
Weighted sum matrix = Pairwise comparison matrix x
Priority vector (1)
1
2
X
X
Xn
=
1 2
a a
an
x
w1
w 2
wn
Consistency vector = Weighted sum matrix/ Priority
vector (2)
1
2
Y
Y
Yn
=
1 2
X X Xn
/
w1
w 2
wn
The method then computes the average of these values
to obtain
ƛmax (3)
Consistency index CI = (ƛmax - n)/(n - 1) (4)
Consistency ratio: CR = CI/RI (5)
RI (Average random consistency) is a function of the
level of the matrix (N), shown in Table 6
Table 6 Average random consistency RI [3]
0
0.0
6
0.9
0
1.1
2
1.2
4
1.3
2
1.4
5
1.4
9
1.5
1
3.3 Decision-making tool
This study uses the VBA programming language
integrated in Excel to build the supporting tool based on
the AHP method The tool is an application that can run
directly on Microsoft Windows versions with simple
module and usage Users run spreadsheet file AHP.xlsx to
start the tool with the main module presented in Figure 1
Users enter alternatives and the related criteria on
"Import Module" in Figure 2
After entering the data, the tool will calculate
automatically and offer the optimal selection in form of
diagrams (Figure 3)
Figure 1 AHP application module
Figure 2 Importmodule 3.4 Case study: Type of bridge selection
In this case study, the topic of a bridge construction project in Quang Nam province is selected The site location already consists of two existing bridges over the river, but due to increased vehicle population and traffic load resulting in frequent traffic congestions the need for another bridge was necessary Proposed bridge should solve the problem of traffic congestion in the area along with the elegant aesthetical appearance
First step of the proposed methodology is to identify important criteria affecting the choice of superstructure and develop best possible alternatives for the project For the identification of criteria Delphi technique is used Eleven top
rated criteria were selected which included Cost (C.), Traffic data (T.D), Hydraulic data (H.D), Environmental impact (E.I), Site selection (S.S) For the development of
alternatives for type of bridge, extensive study of decision problem is required Local authority had done the study through various consultancies and considered three alternatives regarding type of bridge For the study the same alternatives are taken under consideration The six
alternatives are considered namely Segmental bridge (S.B.), Cantilever bridge(C.B.), Cable Stayed Bridge (C.S.), Extradosed bridge (E.B.), Box girder bridge (B.G.), and Arch Bridge (A.B.) for the study
The criteria for evaluating type of bridge are structured
in hierarchy as shown in Figure 4 Based on their own
knowledge and experiences, the experts evaluated the
types Table 7 and Table 8 show the opinions of the
assessments for six types of brigdes for Cost
Each element in the Weighted sum matrix in Table 8 is
calculated in three steps: Calculate the sum of each column
in the pair wise comparison matrix (Table 7),the priority
Trang 458 Pham Anh Duc, Truong Ngoc Son, Vo Van Thuan, Ho Thi Ngoc Nhung, Doan Thi Thu Oanh can be obtained by calculating the ratio of the components
and standardizing values for priority vector
Type of bridge selection
Level 1:
Goal
data Hydraulic data Envirom-enmental impact
Level 2:
Criteria
Level 3:
Types of bridge
S.B.
C.B.
C.S.
E.B.
B.G.
A.B.
Site selection
S.B.
C.B.
C.S.
E.B.
B.G.
A.B.
S.B.
C.B.
C.S.
E.B.
B.G.
A.B.
S.B.
C.B.
C.S.
E.B.
B.G.
A.B.
S.B.
C.B.
C.S.
E.B.
B.G.
A.B.
Figure 4 The structure type of bridge criteria
Figure 3 OutputModule Table 7 Pair-wise comparison matrix for Cost
vector
Table 8 Weighted sum matrix for Cost
B.G 0.305 0.182 0.154 0.121 0.146 0.100
A.B 0.051 0.091 0.077 0.121 0.146 0.100
Priorityvalue of A for experienceis as follows:
∑a11 = 1 + 1/3 + 1 + 4 + 3 + 1/2 = 9.83
W11 = 1
9.83
= 0,102
w1 = 0.102 0.273 0.154 0.091 0.0
6
49 0.2
Calculating similarly for the remaining elements, we
obtain weighted sum vector for Experience
We calculate the consistency ratio, CR, as follows:
- Weighted sum matrix = Pairwise comparison matrix
x Priority vector
0.145
1
1 / 3 1 4 3
1 / 2
+ 0.096
3 1 1 3 2 1
+ 0.146
1 1 1 2 1
1 / 2
+ 0.349
1/ 4 1/ 3 1/ 2 1 1/ 3 1/ 3
+
0.168
1/ 3 1/ 2 1 3 1 1
+ 0.098
2 1 2 3 1 1
=
0.916 0.587 0.924 2.303 1.153 0.623
- Consistency vector = Weighted sum matrix/ Priority vector
0.916 0.145
= 6.317; 0.587
0.096
= 6.115; 0.924
0.146 = 6.329;
2.303 0.349
= 6.599; 1.153
0.168
=6.863; 0.623
0.098
=6.357
We compute the average of these values to obtain ƛmax
ƛmax = 6.317 6.155 6.329 6.599 6.863 6.357
6
=
6.437
- Consistency index:
CI = max
1
n n
=
6.437 6
6 1
= 0.0874 RI=1.24 with n=6
- Consistency ratio:
CR = CI RI
= 0, 00874
1, 24 = 0,07< 0,1 (satisfied)
λmax=6.437; CI=0.0874; CR=0.07 < 0,1 The remaining criteria are estimated for weight sum vector by the same as Cost: Traffic data (T.D), Hydraulic data (H.D), Environmental impact (E.I), Site selection
(S.S) (Table 9 – Table 16) Table 17 and Table 18 show
evaluation and priority between 5 criteria
Table 9 Pair-wise comparison matrix for Traffic data
Traffic
Priority vector
Trang 5ISSN 1859-1531 - THE UNIVERSITY OF DANANG, JOURNAL OF SCIENCE AND TECHNOLOGY, NO 6(115).2017 59
Table 10 Weighted sum matrix for Traffic data
Traffic
B.G 0.370 0.441 0.273 0.324 0.366 0.313
A.B 0.074 0.044 0.091 0.054 0.073 0.063
λmax=6.23; CI=0.05; CR=0.04 < 0,1
Table 11 Pair-wise comparison matrix for Hydraulic data
Hydraulic
Priority vector
Table 12 Weighted sum matrix for Hydraulic data
Hydraulic
B.G 0.377 0.340 0.154 0.288 0.205 0.233
A.B 0.019 0.019 0.051 0.019 0.029 0.033
λmax=6.38; CI=0.08; CR=0.06 < 0,1
Table 13 Pair-wise comparison matrix for Environmental impact
vector
Table 14 Weighted sum matrix for Environmental impact
B.G 0.083 0.034 0.066 0.115 0.065 0.034
A.B 0.083 0.034 0.049 0.154 0.130 0.068
λmax=6.43; CI=0.09; CR=0.07 < 0,1
Table 15 Pair-wise comparison matrix for Site selection
Site
Priority vector
Table 16 Weighted sum matrix for Site selection
Site
B.G 0.070 0.032 0.087 0.043 0.051 0.034
A.B 0.085 0.043 0.174 0.052 0.103 0.068
λmax=6.31; CI=0.06; CR=0.05 < 0,1
Table 17 Pair-wise comparison matrix for 5 criteria
vector
C 1 5 7 2 3 0.439
Table 18 Weighted sum matrix for 5 criteria
C 0.460 0.385 0.368 0.441 0.542
As the value of CR is less than 0.1, the judgments are Acceptable
According to values calculated above, we can obtain
the overall priority of contractors (Table 13)
- Overall priority of contractor S.B = 0.439(0.145) +
0.071(0.087) + 0.055(0.083) + 0,225(0.444) + 0,21(0.372)
= 0,252
- Overall priority of contractor C.B = 0.439(0.096) +
0.071(0.241) + 0.055(0.149) + 0.225(0.143) + 0.21(0.156)
= 0.132
- Overall priority of contractor C.S = 0.439(0.146) +
0.071(0.084) + 0.055(0.410) + 0.225(0.228) + 0.21(0.039)
= 0.152
- Overall priority of contractor E.B = 0.439(0.349) +
0.071(0.175) + 0.055(0.063) + 0.225(0.034) + 0.21(0.294)
= 0.238
Trang 660 Pham Anh Duc, Truong Ngoc Son, Vo Van Thuan, Ho Thi Ngoc Nhung, Doan Thi Thu Oanh
- Overall priority of contractor B.G = 0.439(0.168) +
0.071(0.348) + 0.055(0.266) + 0.225(0.066) + 0.21(0.053)
= 0.139
- Overall priority of contractor A.B = 0.439(0.098) +
0.071(0.067) + 0.055(0.028) + 0.225(0.086) + 0.21(0.088)
= 0.087
Table 19 Priority matrix for prequalified types of bridges
data
Hydraulic
Site selection
Overall Priority vector
As the results of the evaluation by experts and with the
aid of decision-making tool, the analysis results are shown
in Table 19 According to the results of the ranking in Table
20, the types of bridge are now ranked based on their
overall priorities
Table 20 Ranking table
According to the results of the ranking table, the
Segmental bridgeis selected Accurately choosing the most
suitable bridge construction operation is vital for the
success of a bridge project The result demonstrates the
capability and effectiveness of the model that can assist
project contractors to better evaluate bridge construction
methods Notably, the use of the proposed model is not
restricted to the types and numbers of bridge construction
methods The model provides a structured and systematic
approach for effectively identifying the preferred bridge
construction technique It may be applied for different
areas of construction management and solving a large scale
decision-making problem
4 Conclusions and recommendation
Although the AHP method is not unfamiliar, its
application has not been popular in Vietnam This study has
figured out the method of decision-making support through
the AHP and proposed a tool written in VBA programming
language and run in Microsoft Excel spreadsheet software
This study has applied the AHP method combined with
decision support tool to solve a problem in construction
management: selecting the type of bridge
For construction projects with open tendering that
includes many types of bridge and various criteria, the study has found out the type of bridge with the highest weighting that met the requirements from the projects and investors This helps managers make an effective and quick decision of selecting types of bridge This tool could be applied in a wide variety of fields such as Forecasting Finance, Education, Technology, Risk Analysis, Sports, Transportation, Resource Allocation, and many other fields The study supports users in approaching the AHP method and making decisions quickly with the science-based combination of qualitative and quantitative factors
so that users can get best decisions
The implementation of AHP model in the case study has been discussed in the paper, illustrating a successful process conducted by the tool Based on testing, the result figured out by the tool was the same as the result from manual calculation The only difference is that manual calculation is time-consuming, compared to the fast processing speed of the tool Moreover, every user even those who do not have any idea about the AHP concept can use the tool because it processes the data automatically The manual method requires knowledge of formulas, concept as well as AHP-based approach, which not all users can handle In contrast, developing the tool enables users from any background to find accurate and effective solution in a short time
Due to time constraints, this proposed tool has not been totally completed, it just ensures the basic functions of an automated decision support tool Therefore, in the future, the tool needs to be improved about criteria-assessing method and needs an increase of more than two ranks so that it can meet more complex demands of decision-making as well as do surveys of opinions and feedback from experts more quickly and accurately
The tool can be developed in this proposed way: combined with other methods such as the fuzzy sets, TOPSIS combined with VIKOR and AHP can improve the capability of supporting decision-making The researchers are planning to create a web-based model assisting users in updating online criteria in many different fields as well as getting opinions and feedback from professionals immediately This will help the support process become faster The web-based tool and calculating tools developed
in the future will help users find out decisions in the most
accurately, objectively and fastest way
REFERENCES
[1] F Dweiri, S Kumar, S A Khan et al., “Designing an integrated
AHP based decision support system for supplier selection in
automotive industry,” Expert Systems with Applications, vol 62, pp
273-283, 11/15/, 2016
[2] Trần Thị Mỹ Dung, “Tổng quan về ứng dụng phương pháp phân tích
thứ bậc trong quản lý chuỗi cung ứng,” Tạp chí Khoa học, vol 21a,
pp 180-189, 2012
[3] Saaty TL, “The analytic hierarchy process,” New York: McGrawHill, 1980
[4] A.-A Fadwa Gamal Mohammed, and M A Ayu, "Web based multi criteria decision making using AHP method." pp A6-A12 [5] Saaty TL and Vargas LG, “Decision Making in Economic, Political, Social, and Technologycal Environments with the Analytic
Hierarchy Process,” RWS Publication, Pittsburgh, PA, USA, 1994
[6] K.M Al Harbi, “Application of AHP in project management,”
Trang 7ISSN 1859-1531 - THE UNIVERSITY OF DANANG, JOURNAL OF SCIENCE AND TECHNOLOGY, NO 6(115).2017 61
International Journal of Project Management vol 19, no 4, pp
19-27, 2001
[7] M.C.Y Tam and V.M.R Tummala, “An Application of the AHP in
vendor selection of a telecommunications system,” Omega, vol 29,
no 2, pp 171–182, 2001
[8] J Korpela and M Tuominen, “A decision aid in warehouse site
selection,” International Journal of Production Economics, vol 45,
no 1–3, pp 169–180, 1996
[9] M Badri, “Combining the AHP and GP for global facility location–
allocation problem,” International Journal of Production
Economics, vol 62, no 3, pp 237–248, 1999
[10] J Korpela and M Tuominen, “Inventory forecasting with a multiple
criteria decision tool,” International Journal of Production
Economics, vol 45, no 1-3, pp 159–168, 1997
[11] Đặng Thế Ba và Phạm Thị Minh Hạnh, “Hệ thống hỗ trợ ra quyết
định quản lý tổng hợp tài nguyên nước: Thử nghiệm phân tích quản
lý đập Đakmi 4,” Tạp chí khoa học ĐHQGHN, Các Khoa học Trái
Đất và Môi Trường, vol 29, no 2, pp 1-10, 2013
[12] G Büyüközkan, and G Çifçi, “A combined fuzzy AHP and fuzzy TOPSIS based strategic analysis of electronic service quality in
healthcare industry,” Expert Systems with Applications, vol 39, no
3, pp 2341-2354, 2/15/, 2012
[13] J.-F Chen, H.-N Hsieh, and Q H Do, “Evaluating teaching performance based on fuzzy AHP and comprehensive evaluation
approach,” Applied Soft Computing, vol 28, pp 100-108, 3//, 2015
[14] J W M Köksalan, S Zionts, “Multiple criteria decision making
From early history to the 21st century,” World Scientific Publishing
Co Pte Ltd, Singapore 2011
[15] C Musingwini and R.C.A Minnitt, “Ranking the efficiency of selected platinum mining methods using the analytic hierarchy
process (AHP),” Third International Platinum Conference
‘Platinum in Transformation, The Southern African Institute of Mining and Metallurgy, 2008
[16] Saaty TL, “How to make a decision: the analytic hierarchy process,”
European Journal of Operational Research, North-Holland, vol 48,
pp 9-26, 1990
(The Board of Editors received the paper on 21/03/2017, its review was completed on 26/06/2017)