Decision on Roof System Selection
Abstract
can be compromised in order to reach an agreement with other stakeholders. This paper presents group decision model involving three decision-makers on the selection of suitable system for a building’s roof. The objective of the research is to find an agreement options model and coalition algorithms for multi person decision with two main preferences of value which are function and cost. The methodology combines value analysis method using Function Analysis System Technique
(FAST); Life Cycle Cost analysis, group decision analysis method based on Analytical Hierarchy Process (AHP) in a satisfying options, and Game theory-based agent system to develop agreement option and coalition formation for the support system. The support system bridges theoretical gap between automated design in construction domain and automated negotiation in information technology domain by providing a structured methodology which can lead to systematic support system and automated negotiation. It will contribute to value management body of knowledge as an
advanced method for creativity and analysis phase, since the practice of this knowledge is teamwork based. In the case of roof system selection, it reveals the start of the first negotiation round. Some of the solutions are not an option because no individual stakeholder or coalition of stakeholders desires to select it. The result indicates the alternative solution that will be the best-fit solution. In this problem, a space frame system is the ‘best-fit’ solution for the roof system.
INTRODUCTION
his paper provides an approach and develops a
framework for multi person decision in a building
system decision in a case of roof system selection. As a
process involving multi disciplines and teamwork, a
group decision becomes an important role in an element
or a building system selection such as roof system. The
framework is facilitated by the implementation of
coalition formation and it will help to reduce cost and to
improve value of building system decision in
Christiono Utomo is with2 Department of Civil Engineering, FTSP,
Institut Teknologi Sepuluh Nopember, Surabaya, 60111, Indonesia.
E-mail: christiono@ce.its.ac.id.
construction projects. Many researchers suggested
applying Game Theory in multi person decision support
[1]. However, the support model with value criteria has
not been developed. The characteristic of value criteria
cannot be applied to previous research. Existing models
that are commonly accepted are optimization-based
models, for example aggregation methods, but these are
not able to solve the problem of value criteria [2]. This
research applies the satisfying game method where
function and cost of solution techniques as value criteria
can be formulated on coalition algorithms [3].
The roof is one of the most important systems in a
building. No one roofing system meets every buildings
needs, which is why there are so many varieties from
which to choose as the correct one for their building [4].
Support System Model for Value based Group
Decision on Roof System Selection
Christiono Utomo1
Emerging roof technologies complicate product
selection. These products may provide performance
improvements and cost-saving benefits initially as well
as during the life of the roof. Smith argues that knowing
what technologies to consider and what roofing applications
are best-suited for particular buildings makes
selection a complex matter [5]. Identifying the right system
is important for either roofing a new building or reroofing
an existing structure [6]. In new design, the roof
system selection can be part of the building design, for
example, the building can be strengthened to support a
heavy roof system.
The selection process in this case is difficult because of
the large number of factors, many of which are unrelated
or in conflict with one another, and the lack of key data
(such as realistic design service life). The weight of roof
system selection criteria depend on the perspective of the
individual decision-makers [7], for example the architect
might be more interested in the image of the building
function that will be influenced by the roof system,
whereas the project manager or facility manager would
be more interested in domain issues related to the owner
and constraints such as budget that reflected on initial
cost. This makes it difficult for the decision-makers to
agree on the evaluation criteria.
With a general understanding of the available system
options, consideration of the following technical and
non-technical criteria can lead to the selection of the
most appropriate system and details for a project. The
criteria and alternatives of the roof system selection in
this paper are determined from Focus Group research on
the group decision maker in a private developer company
in Indonesia. There are three decision makers involved
which are Architect as Stakeholder 1 (SH1), Facility
Manager as Stakeholder 2 (SH2) and Project Manager as
Stakeholder 3 (SH3). These criteria include initial cost,
maintenance cost, replacement cost, support system,
usability period, functional performance, reliability, and
image. The first three criteria pertain to cost whereas the
other five are relevant to function. It is critical that the
selected system sufficiently satisfies all of the criteria.
There are five possible technical solutions for the roof
system of the building to be selected and evaluated on
eight criteria, by three decision-makers. The alternatives
of technical solution are:
1. Steel structure: steel structure system is one of the
basic methods used in the construction of building
roofs,
2. Pre-cast system: apart from cast in situ concrete
structures, building roofs can also be assembled
from pre-cast members,
3. Timber system: traditionally timber framework is
also used for roof systems,
4. Cast in situ reinforced concrete and
5. Space frame: a space frame or space structure is a
truss-like, lightweight rigid structure constructed
from interlocking struts in a geometric pattern.
Space frames usually utilize a multidirectional span,
and are often used to accomplish long spans with
few supports. Space frames are an increasingly
common architectural technique especially for large
roof spans in modernist commercial and industrial
buildings [8].
A. Value-based Decision
Value-based decision is an effort of Value
Management (VM) process [9]. It improves the value of
a facility through identifying opportunities to remove
unnecessary costs [10]. VM is a structured and analytical
process that seeks to achieve value by identifying all
necessary functions at the lowest cost, while maintaining
with the required levels of quality and performance [11].
It also means that VM identifies and eliminates
unnecessary cost based on function analysis [12].
Unnecessary cost is the nature of design process. VM has
been widely adopted in many countries over several
decades as a very effective tool to meet the increasing
demands for value enhancement by clients [13].
The value based approach as new approach and
methodology that involves using a multidisciplinary
team including representatives of the owner, user,
facility manager, and constructor [9]. The value analysis
is an integrated full team approach [10, 14]. In the
natural characteristic of construction, it means that a tool
for decision team is necessary. Cooperation is the nature
in team work on VM workshop [11]. That decision
analysis techniques can then applied to determine the
relative value of the alternative solutions for performing
function [15]. Weighting and scoring technique are
relevant in value analyses exercise where a decision
needs to be made in selecting an option [16]. A paired
comparison is held to determine the weighing to be given
to each attribute [17]. Many studies in value-based
decision apply multi criteria decision making, such as in
assessment of exterior building wall, in material design
of concrete and in a modification of value engineering in
petrochemical industry [18-20].
B. Cooperative Group Decision
Cooperative Game Theory concepts suited to
decentralize multi task environment in a group decision
[21]. Cooperative games are often defined in terms of a
characteristic function which specifies the outcomes that
each coalition can achieve for itself [22]. For some
decision, outcomes are specified in terms of the total
utility that a coalition can divide (transferable utility).
For other decision, utility is nontransferable that the
achievement of the coalition cannot be characterized by a
single number [21]. A cooperative decision consists of
two elements that are first a set of player N = {1,2,…, n}.
Members of N run from 1 to n. The second is a
characteristic function specifying the value created by
different subsets of the decision makers. The
characteristic function is a function denoted v that
associates with every subset S of N, denoted v(S). In a
cooperative game, it is a pair (N,v), where N is a finite
set and v is a function that maps subsets of N to
members.
C. Coalition and Characteristic Function
This research takes negotiation into consideration in
which decision-makers may choose to cooperate by
forming coalitions. Coalition has been used in many
researches in multi person decision and negotiation and
cooperative games such as for transmission planning in
power system, for cooperative information agent-based
systems, for COTS selection, and who proposed a
coalition approach that identifies and builds sub optimal
yet satisfying coalitions [23-27]. A coalition is any subsetC N , or numbered collection of players in
which there are n>1 players numbered 1, 2, ..., n and set
of all the players N = {1,2,…n}. Coalition is formed by
making binding agreements in order to benefit every
member of the coalition so that all members might
receive more than they could individually on their own.
Since there are n 2 possible subsets of N, there are n 2
possible coalitions. If N= {1, 2} or coalitions with two
members, the possible coalition are n 2 = {0, 1, 2, 12}. In
every coalition there is empty coalition that is a coalition
made up of no members (the null set ) and a grand
coalition N consisting of all the decision makers [27].
The benefit of a coalition can be quantified by
characteristic function. The characteristic function of a
coalition C N is the largest guaranteed payoff to the
coalition. A coalition structure is a means of describing
how the players divide themselves into mutually
exclusive coalitions. It can be described by a set
m S S1, S2,.....,S of the m coalition that is formed.
A multi person decision and negotiation has coalition
formation algorithms. The algorithms can also be
classified into static and dynamic algorithms [28-29].
The general goal for coalition formation is to maximize
utility, but the actual reasons for forming coalitions are
normally different for different decision makers, and
different decisions [22, 29]. There are three varieties of
coalition formation models: the utility-based models [23,
28], knowledge-based model [30-31] and combination
based on both models by [26, 29]. Based on the
characteristic function game this coalition formation
includes three activities which are: generating coalition
structure, solving the optimization problem in each
coalition, and dividing payoff or the value of generated
solution among agents in a fair and stable way so that
agents are motivated to stay within the coalition structure
rather than moving out [32]. Several ways of dividing
payoffs have been proposed in many literatures [33].
METHOD
The methodology for value-based group decision
combines value-based processes, multi-criteria decisionmaking
process, and negotiation base coalition process
[34]. Figure 1 represents these processes. It consists of
three stages base on the process. The first two stages are
referred to [35] and the last stage is based on coalition
formation on Game Theory [1, 23].
The selection of roof system in this paper undergoes
the following steps:
Stage 1: Determining the function and cost of each
technical solution for roof system,
Stage 2: Each decision maker sets the weight of each
criterion (win condition). Using Analytical
Hierarchy Process (AHP) [36], every decision
maker evaluates and ranks the support bridge
options based on his/her win conditions and,
Stage 3: Identifying agreement options that reflect the
combined preferences of all decision makers by
coalition. Finally, determining the ‘best fit’
options for each coalition on first negotiation
RESULTS AND DISCUSSION
A. Stage One: Value-based Process
Value-based process is the first stage on developing of
agreement option and coalition model in this paper [37].
The process of value-based consists of two main stages
which are function analysis and LCC analysis.
1. Function Analysis of Roof System
Function analysis of the roof system is presented in
Figure2. It is developed by team work based on the
Function Analysis System Technique (FAST) method
[12]. There are three basic functions, namely cost of
technical solution, building life cycle support and work
function. These are further divided into eight subfunctions
that will be used as the criteria to select roof
system (F1-F8). Later, the functions are called c1, c2, c3,
f1, f2, f3, f4, and f5 respectively and refer to the
satisfying model of value (function/cost).
2. Life Cycle Cost of Roof System Alternatives
Three cost drivers of the building system which are
initial cost, maintenance cost and replacement cost were
calculated. There is no salvage value on engineering
economics practice in Indonesia. Table 1 presents the
result of Life Cycle Cost (LCC) analysis and the proportion
for each category of initial cost (including investment
cost), operation and maintenance (O&M) cost and
replacement cost. O&M cost is calculated on a yearly
basis. Replacement cost and has variability are calculated
over the period of time.
B. Stage Two: Multi-Criteria Decision Process
The Process consists of three steps namely constructing
decision hierarchy, making judgments and judgment
synthesis, and satisfying of technical solutions on value
criteria. The two first steps follow evaluation process on
Analytical Hierarchy Process (AHP) [36]. The last step
is the evaluation model proposed for this paper. Result
on this process is the ‘best option’ of technical solution
for roof system based on individual decision maker. The
process to determine the ‘best option’ for group is discussed
in next stage.
1. First Step: Constructing Decision Hierarchy
To obtain a good representation of a problem, it has to
be structured into different components called activities.
Figure 3 shows three levels of decision hierarchy. The
goal of the problem (G =Select the best value of
technical solution for roof system for an office building)
is addressed by some alternatives (A = a1; a2; a3; a4; a5)
which are steel structure, pre-cast system, timber system,
reinforced concrete and space frame respectively. The
sub-problems namely cost (LCC) and functions are split
into eight evaluation criteria that will be used to select
the best roof system solution. The evaluations criteria are
c1, c2, c3, f1, f2, f3, f4, and f5 or initial cost,
maintenance cost, replacement cost, support system,
usability period, functional performance, reliability, and
image respectively. Then, implementation of AHP
(Analytical Hierarchy Process) can be started with
compilation of the hierarchy model.
2. Second Step: Making Judgments and Synthesis
The relative importance of pair-wise comparison of
decision input could be: equal (1), moderate (3), strong (5), very strong, demonstrated (7) or extreme (9) [36].
Sometimes one needs to compromise judgments (2; 4; 6;
8) or reciprocal values (1/9; 1/8; 1/7; 1/6; 1/5; 1/4; 1/3;
1/2). If there are n items that need to be compared in a
given matrix, a total of n(n-1)/2 judgments are needed
[36]. For each set of factors, a matrix A of pair-wise
comparison can be derived. There are two judgments
involved in this decision-the first is criteria judgment for
each decision-maker and the second, technical solution
judgment for each criterion.
(1) Criteria judgments for each decision-maker
Based on AHP process, the weighting factor of each
criterion for each decision-maker is calculated. A set of
tables (Table 2, 3, and 4) show the result of pair-wise
comparisons of decision- makers. For example in this
paper, data and analysis of the Architect is presented.
Table 2 shows the preferences of the Architect in a
form of pair-wise comparisons. Table 3 presents the
weighting factor of each criterion based on the
Architect’s preferences. From this table it can be
concluded that the highest ranking of the criteria for
Architect is image, and the lowest is initial cost. Table
IIc shows the calculation of preference consistency on
input judgment. The CR (Consistency Ratio) is 0.08. It is
lower than 0.1, which suggests that the pair-wise input
can be accepted [36]. The calculation and the
relationship between CR, Consistency Index (CI), and
largest eigenvalue (λ) are presented in Table 4.
Using the same procedure presented in Table 2, 3, and
4, the weighting factor of each criterion for the Facility
Manager and Project Manager (PM) Client can be
obtained. Table 5 and Figure 4 presents the result of
criteria judgment for all decision-makers.
The weight of each evaluation criteria for each
decision-maker is different. The difference presents
rationality among decision-maker. The results indicate
that the architect and PM Client contrast in preferences.
The architect argues that image is the most important
criterion in roof system selection, whereas PM client
puts initial cost as the highest priority on the decision of
the roof system.
(2) Technical solution judgment for each criterion
The procedure and calculation for technical solution
judgment is similar with criteria judgment. The goal of
this process is to get the weighting factor of each
technical solution option for each criterion. Table 6, 7,
and 8 shows the judgment input, normalization and
consistency respectively for criteria initial cost (c1).
The results of the technical solution judgments for all
criteria are presented in Figure 5. For example, it can be
seen that for the criterion of initial cost (c1), option RC
(a4) is the cheapest as compared to space frame (a5),
which is the most expensive. Another example is the
criteria of image (f5), where space frame (a5) is the
highest priority. Steel (a1) is the best for the criteria of
functional performance (f3) and reliability (f4).
The goal of judgment synthesis is to get the ranking of
the technical solution option for each decision maker.
The procedure is presented in Table 9.
3. Third Step: Satisfying Option on Value Criteria
Stirling [3] has written and demonstrated satisfying
games on multi-criteria decision-making. He writes that
‘A natural procedure of satisfying options is to separate
the attributes into two categories, one to involve the
attribute that represents functions of an option and the
other to involve attributes that represents losses’.
Categorization of this problem is helpful in identifying
initial, maintenance and replacement costs as ‘Cost’ and
all five function of roof system as ‘Function’. To
compare function and cost representing the value of a
technical solution, they must be represented on the same
scale. This may be done by creating select ability (Ps)
and reject ability (Pr) functions [3] and normalizing the
problem so that the decision-maker has a unit of function
utility and a unit of cost utility to apportion among the
options. The two last columns on Table 10 show the
utility of cost and function for each option of technical
solution.
Based on the results presented in Table 10, Figure 5
provides a cross plot of function and cost, with Pr (reject
ability) the abscissa and Ps (select ability) the ordinate.
The caution index, v, is taken as unity where the
technical solution will be “select” or “reject” if the value
(F/C) is >1 or <1 respectively. Observe that although a4
has the lowest cost, it also has low function, and a
rational decision-maker can legitimately conclude that
this is satisfying, since the function at least outweighs the
costs. Options a3 and a2 is easily eliminated by the costfunction
test. Options a4 here give the highest satisfying
conclusion since it has high function to cost ratio as
defined by [11].
Both the facility manager and project manager are
likely to take into consideration the costs in their
selections. While initial cost is a factor in their decisionmaking
process, it is not the only factor. On the other
hand, the architect considers function in their selection.
Figure 7, 8, and 9 provide a cross plot of function and
cost of each decision-maker.
Observe that the preference value of the decisionmakers
will impact on the value of the technical solution.
The example given here is a5 that has a value greater
than F/C=1 (to select) on the basic value (Figure 5), but
will decrease to less than F/C=1 (to reject) on PM
Client’s preference (Figure 8). This also happens with
a2, in which the architect (Figure 6) gives it a value
greater than F/C=1 (to select), but the Facility Manager
(Figure 7) and Project Manager (Figure 8) decide to
reject.
C. Stage Three: Negotiation base Coalition Process
In this multi person decision with three stakeholder
(Architect, Facility Manager and Project Manager) there
were 8 possible (23) coalitions, including empty coalition
and five singleton coalitions. Agreement options are
determined by conducting five stages, which are;
1. Determining the weighting factor of criteria for each
decision-maker and the aggregation,
2. Grading of alternative for each evaluation criteria,
3. Scoring of each alternative for every decision-maker,
4. Determining the optimal solution (payoff optimum)
and
5. Determining the fitness factor of an alternative
solution
The first three steps came from individual decision
presented in [7]. The results from these first three steps
are used to determine the agreement options in the last
two steps.1. Determining the Optimal Solution (Payoff Optimum)
The determination of the optimal solution for each
decision-maker in a coalition is based on a cooperative
multi-person games with complete information in which
coalition-formation among sub-group members are
allowed [22, 38, 39]. In the context of Game Theory,
they [38-40] presented a proof that the formation of
coalitions among decision-maker provides a means for
achieving Pareto optimality. Coalition formation leads to
an objective function for each decision maker in
coalition Rj, where fi(x) is the payoff of decision-maker i
and gRj(x) is the payoff of coalition Rj, for i Rj. The
variable x in the function of the payoff of decisionmakers
stands for the criteria to be evaluated for the
alternative solutions. Therefore, decision-maker i Rj
maximizes g Rj(x) instead of fi(x) [26]. For every coalition
structure, decision-maker payoffs are determined by
assuming that a rational stakeholder i Rj chooses an
alternative for the group.
Bialas [38] and Wanyama [26] showed that for any
imputation N , ,...., 1 2 , where
i the payoff of
decision-maker i is, therefore
i satisfies the following
Equations:
wP i P i
and i N i G U
(1)
A linear programming formula is used to determine the
Pareto optimal payoff for each decision-maker in each
coalition. A linear programming on Game Theory is used
to determine the payoff players in a coalition [26, 41].
Objective function of the linear programming is min β,
where β
is a measure of deficit that a coalition may
suffer during the distribution of resource (UG) with preemptive
priority, which are total payoff of coalition (P1)
and function of goal constraint every scenario (P2). The
value of P2 comes from mathematical model of styles
and outcomes correlation [7]. There are five constraints.
The first constraint ensures that the total earning of
decision-makers is equal to the available resources. The
second constraint ensures that no decision-maker earns
less than what it can obtain when acting alone. Wanyama
[26] clearly argued that the reason being that if the
decision-maker receives an amount
i < Smin(i), it simply
reject the solution and at worst, earn Smin(i). The third
constraint minimizes the deficit of any coalition. The
fourth constraint is number of coalition member, and the
last constraint ensures that summation of functional
scenario higher than dysfunctional scenario on the
mathematical model of negotiation styles and outcomes
correlation [37].
Based on the linear programming equation, two kinds
of Pareto Optimum payoff can be determined. They
represent the value criteria namely COST payoff
optimum and function payoff optimum. The process to
determine payoff optimum for ‘Cost’ and ‘Function’ is
presented on Table 11 and 12, respectively.
The payoff optimum refers to each decision maker in
each coalition. The value of (max-min) payoff for a
decision maker is used to determine the payoff optimum
by applying the coordinating scenario. This means that
no one stakeholder has higher importance than others.
This scenario can be changed depending on the situation
of a project.
2. Determining the Fitness Factor of an Alternative
Solution
The linear programming formulation yields a Pareto
optimal solution with imputation = (1, 2,.....,N) [42,
43]. Therefore, there are two parameters to determine the
best option, which are the negative value and positive
value. Wanyama [29] determined these values by
comparing decision-maker’s payoffs with Pareto
optimum. Adapted from [26, 42-44], Figure 10 is the
process of fitness factor. The process is applied to both
value criteria namely function and cost. There are two
categorize of best options which are best for function and
best for cost. Based on the two categorize, a best option
for all stakeholder can be determined by value equation
which is Function/Cost. For both value criteria, the best
selectable option is the one with the least negative value.
However, if two alternatives have the same negative
value, then the one with higher positive value of is better.
The rationale is come from [26, 29] that if the negative
value is close to zero, then most decision-makers earn a
payoff close to their Pareto optimum. A high negative
value means that some decision-makers earn higher than
their Pareto optimum. Sets of activities could move,
expand and retract during negotiation [1]. When a
decision maker takes a new alternative, it is purposed to
all users. When a new criterion is taken by a decisionmaker,
this criterion is proposed to the corresponding
group.
The coalition formation model worked in the context of
multi-criteria group decision-making. Firstly, individually
all decision-makers have their own best solution.
Finally, as shown on Table 13, space frame (a5) is found
to be the ‘best fit’ solution for all decision-makers after
coalition. As the ‘best fit’ solution, a1 is contrary to the
best option selected by the project manager and facility
manager, who chose a5. On the process of trade off, the
project manager and facility manager can propose a new
preference if he or she did not accept a5 as the best
option.
IV. CONCLUSION
Firstly, this section presents an overall conclusion of
the research. This is followed by a brief description on
the limitation of the support system model developed in
this research and a brief account of future work in the
areas of multi-criteria multi-person decision making and
its automated system in the domain of value-based
decision, operation research, and agent-based negotiation
and technology.
A. General Conclusion
The coalition table (Table 13) reveals the start of the
first negotiation round. Some of the solutions will not
become an option if no individual stakeholder or
coalition of stakeholders desires to select it. In this case,
alternative solution a2 and a3 was not an option. And the
table indicates the alternative solution that will be the
best-fit solution. In this problem, in the first negotiation
round, a5 was the ‘best-fit’ solution. Stakeholder of
multi-criteria decision making problems usually
evaluates the alternative solution from different perspective,
making it possible to have a dominant solution
among the alternatives. Each stakeholder needs to
identify the goals that can be optimized and those that
12 IPTEK, The Journal for Technology and Science, Vol. 22, No. 1, February 2011
can be compromised in order to reach an agreement with
other stakeholders.
A ‘Value’ in Function/Cost is the basis for the methodology
presented on this paper. On the value-based
process, function and life cycle cost are analyzed. On
multi-criteria decision-making, a satisfying option is
used by correlating the function and cost to get the value
of a technical solution option. On multi person decision
process, the payoff optimum and best fit options are
based on the criterion of value, which are function and
cost. In this proposed model, a multi person decision
consists of exchange of proposals between decisionmakers.
When decision-maker i proposes its alternative
to decision-maker j, this alternative should be the most
preferred alternative for decision-maker j (with the
highest priorities with respect to the goal) to accept it
immediately. If not, decision maker j tries to change the
alternatives order of preference by adjusting judgments
in pair-wise comparison matrices. If the proposal is not
accepted, it will send a counter-proposal. Sets of activities
could move, expand and retract during group
decision process.
B. Recommendation for Future Research
The research was deliberately limited towards
addressing the ‘value’ in the component of value for
money. There are many issues relating to the difficulties
of cost modeling which have not been addressed. The
adopted research strategy is also open to criticism on the
basis that it focused only on roof system selection. It is
also important to point out that there are significant
differences between the subjective interpretation of the
researcher and an inter-subjective interpretation amongst
the decision makers. Once the paradigm of positivist
research is rejected, there is no longer any objective
reality against which to measure validity.
This paper has developed the theoretical and
philosophical basis of negotiation support. There is
considerable amount of work which remains to be done
within the wider domains of building economics,
construction management, operation research and agentbased
negotiation and technology. There is need for
further research into the possible application of other
methodologies of group decision support and negotiation
support. In the domain of operation research, there are a
lot of opportunities for mathematical proof research for
optimization and satisfying decision in cooperative and
incomplete information environments. A mathematical
proof research for an unlimited multi-person decision
maker in a project involving a whole community will be
an interesting research.
Future research in the field of agent-based negotiation
and management will have a huge benefit from the
development of a user-friendly software which uses a
GUI (graphical user interface), but it will surely consume
a lot of time and money for research. In future, the
combination of many technologies such as Virtual
Reality (VR) will help human and its agent to
communicate, discuss and make decision for any type or
stages of building system design with two main
important preferences that are function and cost. As to
further illustrate, a final building design decision can be
made by an agent from all the project participants in a
virtual reality environment simultaneously while being in
a different geographical area.
The recommended future works associated with the
research reported in this paper are as follows:
1. To integrate the support for elicitation process with
technical solution selection. It needs to develop
ontology of functional concept of building system
product alternatives. At present, such ontology is not
available. The work to develop ontology of functional
concept has been started by [45] but until now
researches in this area are still in its very preliminary
stage.
2. To extend the framework of technical solution to
address the issue of selecting multiple building (roof)
system products alternatives to perform the function.
It will be run concurrently between satisfying games
method to reduce the number of technical solution
and optimization games method to select the best fit
for the technical solutions. Research and practice in
the objectives area of decision making science to
reduce alternatives are still in the qualitative stages,
such as advantage and disadvantages analysis, and
benchmark analysis.
3. To continue developing, modifying and testing the
agent negotiation protocol of the support system and
reasoning mechanism. Time constraint will be
important criteria to be considered.
4. To continue working on multi-attribute decision
making, specifically on the process of eliciting user
preference models such as neural network application
and value function, and on establishing expert
quantitative data from qualitative description of the
feature of the alternative solution. It will need the
development of trade off algorithms to analyze value
of technical solution (roof system) in real time.
5. To develop knowledge management properties on the
model to store the selection data and information in
various types of repositories such as system selection
repository, user repository, discussion repository,
lessons learn repository, and historical information
repository.
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TRANSLATE
LATAR BELAKANG
kelompok sistem pendukung keputusan
diperlukan pada keputusan berbasis nilai karena ada kekhawatiran yang berbeda disebabkan oleh perbedaan preferensi,
pengalaman, dan latar belakang. Hal ini untuk memungkinkan setiap pengambil
keputusan untuk mengevaluasi dan peringkat alternatif solusi sebelum terlibat dalam
negosiasi dengan para pengambil keputusan lainnya. Stakeholder keputusan multi
kriteria membuat masalah biasanya mengevaluasi
solusi alternatif dari perspektif yang berbeda, sehingga memungkinkan untuk
memiliki solusi dominan di antara alternatif.
Setiap pemangku kepentingan perlu mengidentifikasi tujuan yang dapat
dioptimalkan dan orang-orang yang dapat dikompromikan untuk mencapai
kesepakatan dengan para pemangku kepentingan lainnya. Makalah ini menyajikan
model keputusan kelompok
melibatkan tiga pengambil keputusan pada
pemilihan sistem cocok untuk atap bangunan. Tujuan dari penelitian ini adalah
untuk menemukan pilihan kesepakatan Model dan
algoritma koalisi keputusan multi-orang dengan dua preferensi utama nilai
yang fungsi dan biaya. Metodologi ini
menggabungkan metode analisis nilai menggunakan Fungsi Analisis Sistem Teknik (FAST); Analisis biaya Siklus Hidup,
metode analisis keputusan kelompok berdasarkan Analytical Hierarchy Process
(AHP) dalam Pilihan memuaskan, dan Game berbasis
teori sistem agen untuk mengembangkan pilihan perjanjian dan pembentukan koalisi
untuk sistem pendukung. Sistem pendukung
menjembatani kesenjangan teoritis antara desain otomatis dalam domain
konstruksi dan otomatis negosiasi di domain teknologi
informasi dengan menyediakan metodologi terstruktur yang dapat menyebabkan sistem pendukung sistematis dan
negosiasi otomatis. Ini akan memberikan kontribusi untuk menghargai manajemen
tubuh pengetahuan sebagai Metode canggih untuk kreativitas dan
tahap analisis, karena praktek pengetahuan ini adalah kerja sama tim berbasis.
Dalam kasus
pemilihan sistem atap, mengungkapkan
awal negosiasi putaran pertama. Beberapa solusi yang bukan pilihan karena tidak
ada pemangku kepentingan individu atau
koalisi stakeholder keinginan untuk memilihnya. Hasilnya menunjukkan solusi
alternatif yang akan menjadi yang terbaik-fit solusi. Dalam
masalah ini, sistem space frame adalah solusi 'best-fit' untuk sistem atas
METODE
A. Tahap Satu: Proses-Nilai berdasarkan
Proses-nilai berdasarkan adalah tahap pertama pada pengembangan dari
Pilihan kesepakatan dan model koalisi dalam makalah ini [37].
Proses berbasis nilai terdiri dari dua tahap utama
yang analisis fungsi dan analisis LCC.
1. Fungsi Analisis Sistem Atap
Analisis fungsi dari sistem atap disajikan dalam
Figure2. Hal ini dikembangkan oleh tim kerja berdasarkan
Teknik Analisis Sistem fungsi metode (FAST)
[12]. Ada tiga fungsi dasar, yaitu biaya
solusi teknis, membangun kehidupan dukungan siklus dan bekerja
fungsi. Ini dibagi lagi menjadi delapan subfunctions
yang akan digunakan sebagai kriteria untuk memilih atap
sistem (F1-F8). Kemudian, fungsi disebut c1, c2, c3,
f1, f2, f3, f4, f5 dan masing-masing dan mengacu pada
Model memuaskan nilai (fungsi / biaya).
Siklus Biaya 2. Hidup Atap Sistem Alternatif
Tiga driver biaya sistem bangunan yang
biaya, biaya pemeliharaan dan penggantian biaya awal yang
dihitung. Tidak ada nilai sisa pada rekayasa
praktek ekonomi di Indonesia. Tabel 1 menyajikan
Hasil Siklus Hidup Biaya (LCC) analisis dan proporsi
untuk setiap kategori biaya awal (termasuk investasi
biaya), operasi dan pemeliharaan (O & M) biaya dan
biaya penggantian. O & M biaya dihitung pada tahunan
dasar. Biaya penggantian dan memiliki variabilitas dihitung
selama periode waktu.
B. Tahap Dua: Multi-Kriteria Proses Keputusan
Proses ini terdiri dari tiga langkah yaitu membangun
keputusan hirarki, membuat penilaian dan penghakiman
sintesis, dan memuaskan dari solusi teknis nilai
kriteria. Dua langkah pertama mengikuti proses evaluasi
Analytical Hierarchy Process (AHP) [36]. Langkah terakhir
adalah model evaluasi yang diusulkan untuk makalah ini. Hasil
pada proses ini adalah 'pilihan terbaik' dari solusi teknis
untuk sistem atap berdasarkan pengambil keputusan individu. The
Proses untuk menentukan 'pilihan terbaik' untuk Gro
1. Langkah Pertama: Membangun Keputusan Hierarchy
Untuk mendapatkan representasi yang baik dari masalah, itu harus
terstruktur menjadi komponen yang berbeda yang disebut kegiatan.
Gambar 3 menunjukkan tiga tingkat hirarki keputusan. The
Tujuan dari masalah (G = Pilih nilai terbaik
solusi teknis untuk sistem atap untuk gedung perkantoran)
ditujukan oleh beberapa alternatif (A = a1; a2; a3; a4; a5)
yang struktur baja, sistem pre-cast, sistem kayu,
beton bertulang dan space frame masing-masing. The
sub-masalah yaitu biaya (LCC) dan fungsi dibagi
menjadi delapan kriteria evaluasi yang akan digunakan untuk memilih
solusi terbaik sistem atap. Kriteria evaluasi yang
c1, c2, c3, f1, f2, f3, f4, f5 dan atau biaya awal,
biaya pemeliharaan, biaya penggantian, sistem pendukung,
periode kegunaan, kinerja fungsional, kehandalan, dan
gambar masing-masing. Kemudian, pelaksanaan AHP
(Analytical Hierarchy Process) dapat dimulai dengan
kompilasi dari model hirarki.
2. Langkah kedua: Membuat Penghakiman dan Sintesis
Kepentingan relatif dari perbandingan pasangan-bijaksana
masukan keputusan bisa menjadi: sama (1), sedang
(3), kuat
KESIMPULAN
Banyak peneliti menyarankan
menerapkan Teori Permainan mendukung keputusan orang yang multi
[1]. Namun, model dukungan dengan kriteria nilai memiliki
belum dikembangkan. Karakteristik kriteria nilai
tidak dapat diterapkan untuk penelitian sebelumnya. Model yang ada
yang umum diterima yang berbasis optimasi
model, untuk metode misalnya agregasi, tetapi ini
tidak mampu memecahkan masalah kriteria nilai [2]. Ini
Penelitian menggunakan metode permainan yang memuaskan di mana
fungsi dan biaya teknik solusi sebagai kriteria nilai
dapat dirumuskan pada algoritma koalisi [3].
Atap adalah salah satu sistem yang paling penting dalam
bangunan. Tidak ada sistem satu atap memenuhi setiap bangunan
kebutuhan, itulah sebabnya mengapa ada begitu banyak varietas dari
yang untuk memilih sebagai yang benar untuk membangun mereka [4].
Sistem dukungan Model Group yang berbasis Nilai
Keputusan Roof Sistem Seleksi
Christiono Utomo1
T
Teknologi atap muncul mempersulit produk
seleksi. Produk-produk ini dapat memberikan kinerja
perbaikan dan manfaat penghematan biaya awalnya juga
seperti pada kehidupan atap. Smith berpendapat bahwa mengetahui
apa teknologi untuk mempertimbangkan dan apa aplikasi atap
yang terbaik cocok untuk bangunan tertentu membuat
Temukan masalah yang kompleks [5]. Mengidentifikasi sistem yang tepat
penting untuk baik atap sebuah bangunan baru atau reroofing
struktur yang ada [6]. Dalam desain baru, atap
sistem seleksi dapat menjadi bagian dari desain bangunan, untuk
Misalnya, bangunan dapat diperkuat untuk mendukung
sistem atap yang berat.
Proses seleksi dalam hal ini adalah sulit karena
jumlah besar faktor, banyak yang tidak terkait
atau bertentangan dengan satu sama lain, dan kurangnya data kunci
(seperti desain kehidupan pelayanan realistis). Berat atap
kriteria seleksi sistem tergantung pada perspektif
pengambil keputusan individu [7], misalnya arsitek
mungkin akan lebih tertarik pada gambar bangunan
Fungsi yang akan dipengaruhi oleh sistem atap,
sedangkan manajer proyek atau manajer fasilitas akan
lebih tertarik pada isu-isu yang berkaitan dengan domain pemilik
dan kendala seperti anggaran yang tercermin pada awal
biaya. Hal ini membuat sulit bagi pengambil keputusan untuk
menyepakati kriteria evaluasi.
Dengan pemahaman umum dari sistem yang tersedia
pilihan, pertimbangan teknis berikut dan
Kriteria non-teknis dapat menyebabkan pemilihan
sistem yang paling tepat dan detail untuk sebuah proyek. The
kriteria dan alternatif pilihan sistem atap di
makalah ini ditentukan dari penelitian Focus Group on
pembuat keputusan kelompok di sebuah perusahaan pengembang swasta
di Indonesia. Ada tiga pengambil keputusan yang terlibat
yang Arsitek sebagai Stakeholder 1 (SH1), Fasilitas
Manajer sebagai Stakeholder 2 (SH2) dan Project Manager sebagai
Stakeholder 3 (SH3). Kriteria ini meliputi biaya awal,
biaya pemeliharaan, biaya penggantian, sistem pendukung,
periode kegunaan, kinerja fungsional, kehandalan, dan
image. Tiga kriteria pertama berkaitan dengan biaya sedangkan
Lima lainnya yang relevan berfungsi. Sangat penting bahwa
Sistem yang dipilih cukup memenuhi semua kriteria.
Ada lima Solusi Teknis Yang mungkin untuk review atap
Sistem Bangunan Yang dipilih akan dievaluasi Dan
Kriteria Delapan , Tiga Diposkan Pengambil Keputusan . alternatif
Solusi Teknis Adalah :
1. Baja Struktur : Sistem Struktur baja Adalah shalat Satu
Metode Dasar Yang digunakan hearts Pembangunan gedung
atap ,
2. Pra -Cast Sistem : terpisah Dari cor beton in situ
Struktur , atap Bangunan JUGA DAPAT dirakit
Dari ANGGOTA pra -Cast ,
Sistem 3. Kayu : tradisional Kerangka kayu Adalah
JUGA digunakan untuk review atap sistem plc,
4. Cast in situ beton bertulang Dan
Bingkai 5. Space: Struktur Rangka ATAU Ruang angkasa Adalah
truss seperti , Struktur kaku Ringan dibangun
Dari saling struts geometris hearts Pola .
Bingkai Ruang biasanya memanfaatkan Rentang multi
Dan Sering digunakan untuk review mencapai bentang Panjang DENGAN
beberapa Dukungan . Bingkai Ruang Adalah Semakin
teknik Arsitektur Umum terutama gede untuk review
atap membentang di modernis Komersial dan Industri
Bangunan [ 8 ]
Ada lima solusi teknis yang mungkin untuk atap
sistem bangunan yang akan dipilih dan dievaluasi
delapan kriteria , oleh tiga pengambil keputusan . alternatif
solusi teknis adalah:
1. Baja Struktur : sistem struktur baja adalah salah satu
Metode dasar yang digunakan dalam pembangunan gedung
atap ,
2. Pre -cast sistem : terpisah dari cor beton in situ
struktur , atap bangunan juga dapat dirakit
dari anggota pra -cast ,
Sistem 3. Kayu : tradisional kerangka kayu adalah
juga digunakan untuk sistem atap ,
4. Cast in situ beton bertulang dan
Bingkai 5. Space: struktur rangka atau ruang angkasa adalah
truss seperti , struktur kaku ringan dibangun
dari saling struts dalam pola geometris .
Frame ruang biasanya memanfaatkan rentang multi ,
dan sering digunakan untuk mencapai bentang panjang dengan
beberapa dukungan . Frame ruang adalah semakin
teknik arsitektur umum terutama untuk besar
atap membentang di modernis komersial dan industri
bangunan [ 8 ] .
Keputusan A. Nilai berbasis
Keputusan - nilai berdasarkan merupakan upaya dari nilai
Manajemen ( VM ) proses [ 9 ] . Ini meningkatkan nilai
fasilitas melalui mengidentifikasi peluang untuk menghapus
biaya yang tidak perlu [ 10 ] . VM adalah terstruktur dan analitis
proses yang berusaha untuk mencapai nilai dengan mengidentifikasi semua
fungsi yang diperlukan pada biaya terendah , dengan tetap menjaga
dengan tingkat yang diperlukan kualitas dan kinerja [ 11 ] .
Ini juga berarti bahwa VM mengidentifikasi dan menghilangkan
biaya yang tidak perlu didasarkan pada analisis fungsi [ 12 ] .
Biaya yang tidak perlu adalah sifat dari proses desain . VM memiliki
diadopsi secara luas di banyak negara selama beberapa
dekade sebagai alat yang sangat efektif untuk memenuhi meningkatnya
tuntutan untuk peningkatan nilai dengan klien [ 13 ] .
Pendekatan nilai berdasarkan sebagai pendekatan baru dan
metodologi yang melibatkan menggunakan multidisiplin sebuah
Tim termasuk perwakilan dari pemilik , pengguna ,
manajer fasilitas , dan konstruktor [ 9 ] . Analisis nilai
adalah terintegrasi pendekatan tim penuh [ 10 , 14 ] .
Pendekatan nilai berdasarkan sebagai pendekatan baru dan
metodologi yang melibatkan menggunakan multidisiplin sebuah
Tim termasuk perwakilan dari pemilik, pengguna,
manajer fasilitas, dan konstruktor [9]. Analisis nilai
adalah terintegrasi pendekatan tim penuh [10, 14]. Dalam
karakteristik alami dari konstruksi, itu berarti bahwa alat
keputusan tim diperlukan. Kerjasama adalah sifat
dalam pekerjaan tim pada VM lokakarya [11]. Keputusan itu
teknik analisis kemudian dapat diterapkan untuk menentukan
nilai relatif dari solusi alternatif untuk melakukan
fungsi [15]. Pembobotan dan teknik scoring yang
relevan dalam nilai analisis latihan di mana keputusan
perlu dibuat dalam memilih opsi [16]. Sebuah dipasangkan
perbandingan diadakan untuk menentukan berat untuk diberikan
untuk setiap atribut [17]. Banyak penelitian nilai berbasis
Keputusan menerapkan kriteria pengambilan keputusan multi seperti di
penilaian dinding eksterior bangunan, dalam desain bahan
beton dan di modifikasi rekayasa nilai dalam
industri petrokimia [18-20].
Keputusan B. Cooperative Group
Koperasi Permainan konsep Teori cocok untuk
desentralisasi lingkungan multi tugas dalam keputusan kelompok
[21]. Permainan kooperatif sering didefinisikan dalam hal
fungsi karakteristik yang menentukan hasil yang
masing-masing koalisi dapat mencapai sendiri [22]. Untuk beberapa
keputusan, hasil yang ditentukan dalam hal total
utilitas yang koalisi dapat membagi (utilitas dipindahtangankan).
Untuk keputusan lainnya, utilitas adalah dialihkan bahwa
pencapaian koalisi tidak dapat ditandai dengan
nomor tunggal [21]. Sebuah keputusan koperasi terdiri dari
dua elemen yang pertama seperangkat pemain N = {1,2, ..., n}.
Anggota N berjalan dari 1 sampai n. Yang kedua adalah
fungsi karakteristik menentukan nilai yang diciptakan oleh
himpunan bagian yang berbeda dari para pengambil keputusan. The
fungsi karakteristik adalah fungsi dilambangkan v yang
asosiasi dengan setiap bagian S dari N, dilambangkan v (S). Di sebuah
permainan kooperatif, itu adalah sepasang (N, v), di mana N adalah terbatas
mengatur dan v adalah fungsi yang memetakan himpunan bagian dari N ke
anggota.
C. Koalisi dan Karakteristik Fungsi
Penelitian ini mengambil negosiasi menjadi pertimbangan dalam
yang pengambil keputusan dapat memilih untuk bekerja sama dengan
membentuk koalisi. Koalisi telah digunakan di banyak
penelitian dalam keputusan orang yang multi dan negosiasi dan
permainan kooperatif seperti untuk perencanaan transmisi di
sistem tenaga, untuk informasi koperasi berbasis agen
sistem, untuk COTS seleksi, dan yang mengusulkan
Pendekatan koalisi yang mengidentifikasi dan membangun sub optimal
koalisi belum memuaskan
