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层次分析法
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文
献翻译
888
大学
毕业设计
(
论文
)
< br>文献翻译
题
目
层次分析法
院、系
(
部
)
计算机科学与技术学院
专业及班级
计科
0903
班
姓
名
888
指
导
教
师
888
日
期
20
13
年
3
月
Analytic Hierarchy Process
The Analytic Hierarchy Process (AHP) is
a structured technique for
helping
people deal with complex decisions.
Rather than prescribing a
their needs and wants. Based
on mathematics and psychology, it was
developed by Thomas L. Saaty in the
1970s and has been extensively
studied
and refined since then. The AHP provides a
comprehensive and
rational framework
for structuring a problem, for representing and
quantifying its elements, for relating
those elements to overall goals,
and
for evaluating alternative solutions. It is used
throughout the
world in a wide variety
of decision situations, in fields such as
government, business, industry,
healthcare, and education.
Several
firms supply computer software to assist in using
the
process.
Users of the
AHP first decompose their decision problem into a
hierarchy of more easily comprehended
sub-problems, each of which can be
analyzed independently. The elements of
the hierarchy can relate to any
aspect of the decision
problem
—
tangible or
intangible, carefully
measured or
roughly estimated, well- or poorly-
understood
—
anything at
all that applies to the decision at
hand.
Once the hierarchy is built, the
decision makers systematically
evaluate
its various elements, comparing them to one
another in pairs.
In making the
comparisons, the decision makers can use concrete
data
about the elements, or they can
use their judgments about the elements'
relative meaning and importance. It is
the essence of the AHP that human
judgments, and not just the underlying
information, can be used in
performing
the evaluations.
The AHP converts
these evaluations to numerical values that can be
processed and compared over the entire
range of the problem. A numerical
weight or priority is derived for each
element of the hierarchy,
allowing
diverse and often incommensurable elements to be
compared to
one another in a rational
and consistent way. This capability
distinguishes the AHP from other
decision making techniques.
In the
final step of the process, numerical priorities
are derived
for each of the decision
alternatives. Since these numbers represent the
alternatives' relative ability to
achieve the decision goal, they allow
a
straightforward consideration of the various
courses of action.
Uses and
applications
While it can be used by
individuals working on straightforward
decisions, Analytic Hierarchy Process
(AHP) is most useful where teams
of people are working on
complex problems, especially those with high
stakes, involving human perceptions
and judgments, whose resolutions have
long-term repercussions. It
has unique
advantages where important elements of the
decision are
difficult to quantify or
compare, or where communication among team
members is impeded by their different
specializations, terminologies, or
perspectives.
Decision
situations to which the AHP can be applied
include:
, Choice - The selection of
one alternative from a given set of
alternatives,
usually where
there are multiple decision criteria involved.
, Ranking - Putting a set of
alternatives in order from most to
least
desirable
Prioritization - Determining the relative merit of
a set
of
alternatives, as
opposed to selecting a single one or merely
ranking
them
, Resource
allocation - Apportioning resources among a set of
alternatives
, Benchmarking
- Comparing the processes in one's own
organization
with
those of
other best-of-breed organizations
,
Qualitymanagement - Dealing with the
multidimensional aspects of
quality
and quality improvement
The applications of AHP to complex
decision situations have numbered
in
the thousands, and have produced extensive results
in problems
involving planning,
Resource allocation, priority setting, and
selection
among alternatives. Other
areas have included forecasting, toreotal
quality management, business process
re-engineering ,quality function
deployment
，
and
the Balanced
AHP applications are
never reported to the world at large, because
they take place at high levels of large
organizations where security and
privacy considerations prohibit their
disclosure. But some uses of AHP
are
discussed in the literature. Recently these
have included:
, Deciding
how best to reduce the impact of global climate
change
(Fondazione Eni Enrico Mattei)
, Quantifying the overall quality of
software system(Microsoft
corporation)
, Selecting university
faculty(Bloomsburg University of Pennsy)
, Deciding where to locate offshore
manufacturing plants(University
of
Cambridge)
, Assessing risk
in operating cross-country prtroleum
pipelines(American
Society
of Civil Engineers)
, Deciding how
best to manage U.S. watersheds(U.S. Department of
Agriculture)
AHP is sometimes used in designing
highly specific procedures for
particular situations, such as the
rating of buildings by historic
significance. It was recently applied
to a project that uses video
footage to
assess the condition of highways in
Virginia. Highway engineers first used
it to determine the optimum
scope of
the project, then to justify its budget to
lawmakers.
AHP is widely used in
countries around the world. At a recent
international conference on AHP, over
90 papers were presented from 19
countries, including the U.S., Germany,
Japan, Chile , Malaysia,
andNepal.
Topics covered ranged from Establishing Payment
Standards for
Surgical Specialists, to
Strategic Technology
Roadmapping, to
Infrastructure Reconstruction in Devastated
Countries. AHP was
introduced in China in 1982, and its
use in that country has
expanded
greatly since then
—
its
methods are highly compatible with the
traditional Chinese decision making
framework, and it has been used for
many decisions in the fields
ofeconomics,energy,management,environment,traffi c,agriculture,
industry, and the
military.
Though using AHP requires no
specialized academic trainning, the
subject is widely taught at the
university level
—
one AHP
software
provider lists over a hundred
colleges and universities among its
clients. AHP is considered an
important
subject in many institutions of higher learning,
including
schools of engineering and Graduate
school of Business . AHP is also an
important subject in the quality field,
and is taught in many
specialized
courses including Six Sigma, Lean Six Sigma, and
QFD.
In China, nearly a hundred
schools offer courses in AHP, and many
doctoral students choose AHP as the
subject of their research and
dissertations. Over 900 papers have
been published on the subject in
that
country, and there is at least one Chinese
scholarly journal
devoted exclusively
to AHP.
Implementation
As
can be seen in the examples that follow, using the
AHP involves
the mathematical synthesis
of numerous judgments about the decision
problem at hand. It is not uncommon for
these judgments to number in the
dozens
or even the hundreds. While the math can be done
by hand or with
a calculator, it is far
more common to use one of several computerized
methods for entering and synthesizing
the judgments. The simplest of
these
involve standard spreadsheet software, while the
most complex use
custom software, often
augmented by special devices for acquiring the
judgments
of decision
makers gathered in a meeting room.
Steps in using the process
The procedure for using the AHP can be
summarized as:
1. Model the problem as
a hierarchy containing the decision goal,
the alternatives
for
reaching it, and the criteria for evaluating the
alternatives.
2. Establish priorities among the
elements of the hierarchy by
making a
series of
judgments based on pairwise
comparisons of the elements. For example,
when
comparing potential
real-estate purchases, the investors might say
they prefer
location over
price and price over timing.
3.
Synthesize these judgments to yield a set of
overall priorities
for the hierarchy.
This would combine the investors'
judgments about location, price
and
timing
for properties A, B, C, and D
into overall priorities for each
property.
4. Check the
consistency of the judgments.
5. Come
to a final decision based on the results of this
process.
Criticisms
The
AHP is now included in most operations research
and management
science textbooks, and
is taught in numerous universities; it is used
extensively in organizations that have
carefully investigated its
theoretical
underpinnings. While the general consensus is that
it is
both technically valid and
practically useful, the method does have its
critics.
In the early 1990s a series of debates
between critics and
proponents of AHP
was published in Management Science and The
Journal of
the Operational Research
Society. These debates seem to have
been settled in favor of AHP.
Occasional criticisms still appear. A
1997 paper examined possible
flaws in
the verbal (vs. numerical) scale often used in AHP
pairwise
comparisons. Another from the
same year claimed that innocuous changes
to the AHP model can introduce order
where no order exists. A 2006 paper
found that the addition of criteria for
which all alternatives perform
equally
can alter the priorities of alternatives. An in-
depth paper
discussing the academic
criticisms of AHP was published in Operations
Research in
2001.
Most of the criticisms involve a
phenomenon called rank reversal,
discussed in
the following
section.
Rank reversal
Many people hear about rank reversal
and assume that there is some
sort of
proven principle about it that needs to be upheld
in making
decisions. That assumption
has led to much misunderstanding of AHP and
other decision making techniques. In
actuality, rank reversal is a
complex
matter about which there are many conflicting
ideas and opinions.
This section offers
a simplified explanation of the situation.