Uncertainties in the AnalyticHierarchyProcess
Among the bewildering array of decision analysis techniques that apply systematic and structured analysis to complex decisions, the AnalyticHierarchyProcess (AHP) is one of the most widely used. From the early days it has been noted that it can result in certain anomalies, the rank reversal problem being the most widely known. Whether or not these behavioural anomalies are actually reflected in real-world decision makers has been a topic of hot discussion. In the case of rank reversal, many authors believe that it is valid in certain real-world situations; but besides rank reversal there are other anomalies that are harder to justify. When choosing a decision analysis technique to model a particular complex decision, the fundamentals of the technique should be understood by the analyst, and they should be appropriate for the characteristics of the problem itself. When a problem cannot be decomposed into independent facets, for example, then a model that requires criteria independence such as the AHP should not be applied.
Abstract—Continuous evaluation of instructors’
effectiveness and courses’ relevance constitute an important part of the educational Process. In this paper, the AnalyticHierarchyProcess (AHP) is used for the Ranking of the following University Courses: Introduction to Computing, Business Statistics and Financial Mathematics. The data for using the AHP model are 482 Greek university students’
The AnalyticHierarchyProcess (AHP) is a powerful and flexible decision making process to help people set priorities and make the best decision when both qualitative and quantitative aspects of a decision need to be considered. By reducing complex decisions to a series of one-on-one comparisons, then synthesizing the results, AHP not only helps decision makers arrive at the best decision, but also provides a clear rationale that it is the best.
In a world whose complexity is rapidly growing, making the best decisions becomes an increasingly demanding task for managers of companies, governmental agencies and many other decision and policy makers. In recent years, this has gone arm-in-arm with the growth of what are now known as decision analytics methodologies. Namely, decision makers are more reluctant to make gut decisions based of feelings and hunches, and instead prefer to use analytic and quantitative tools, and base and analyze their decisions on a solid ground. Many methods stemming from applied mathematics and operations research have proved useful to help decision makers making informed decisions, and among these methods there are also those requiring, as inputs, subjective judgments from a decision maker or an expert. It is in this context that the AnalyticHierarchyProcess (AHP) becomes a useful tool for analyzing decisions.
Introduction to AnalyticHierarchyProcess
The AHP (AnalyticHierarchyProcess) was developed by Thomas L. Saaty (1980) and is the well-known and useful method to obtain weights of each alternative in a multiple criteria decision-making problem. AHP requires the decision maker to provide judgments about the relative importance of each criterion, and then, specify a preference for each decision alternative using each criterion. The output of AHP is a prioritized ranking of the decision alternatives based on the overall preferences expressed by the decision maker.
This article presents a literature review of the applications of AnalyticHierarchyProcess (AHP). AHP is a multiple criteria decision-making tool that has been used in almost all the applications related with decision-making. Out of many diﬀerent applications of AHP, this article covers a select few, which could be of wide interest to the researchers and practitioners. The article critically analyses some of the papers published in international journals of high repute, and gives a brief idea about many of the referred publications. Papers are categorized according to the identiﬁed themes, and on the basis of the areas of applications. The references have also been grouped region-wise and year-wise in order to track the growth of AHP applications. To help readers extract quick and meaningful information, the ref- erences are summarized in various tabular formats and charts.
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Abstract: Decisions involve many intangibles that need to be traded off. To do that, they have to be measured along side tangibles whose measurements must also be evaluated as to, how well, they serve the objectives of the decision maker. The AnalyticHierarchyProcess (AHP) is a theory of measurement through pairwise comparisons and relies on the judgements of experts to derive priority scales. It is these scales that measure intangibles in relative terms. The comparisons are made using a scale of absolute judgements that represents, how much more, one element dominates another with respect to a given attribute. The judgements may be inconsistent, and how to measure inconsistency and improve the judgements, when possible to obtain better consistency is a concern of the AHP. The derived priority scales are synthesised by multiplying them by the priority of their parent nodes and adding for all such nodes. An illustration is included.
Keywords: Analytichierarchyprocess, AHP, Risk management, Decision making (processes), Multiple criteria decision.
A decision exercise evaluates and ranks alternatives with respect to an objective. Save for the trivial cases, the decisions are based on the aggregated effects of a number of criteria. Quantitative decision methods compute scores for the alternatives to rank them. A score either reflects the level of benefit that the alternative delivers or it determines the cost of the alternative. AnalyticHierarchyProcess (AHP) (Saaty, 1982) is a popular and pragmatic quantitative decision method. It provides a practical method to transform comparative descriptions of the problem elements into weights for the selection criteria and scores for the alternatives.
AnalyticHierarchyProcess (AHP) is one of Multi Criteria decision making method that was originally developed by Prof. Thomas L. Saaty. In short, it is a method to derive ratio scales from paired comparisons. The input can be obtained from actual measurement such as price, weight etc., or from subjective opinion such as satisfaction feelings and preference. AHP allow some small inconsistency in judgment because human is not always consistent. The ratio scales are derived from the principal Eigen vectors and the consistency index is derived from the principal Eigen value.
[Preprint version] Please cite as “Ishizaka Alessio, Labib Ashraf, AnalyticHierarchyProcess and
Expert Choice: Benefits and Limitations, ORInsight, 22(4), p. 201–220, 2009” 18 Triantaphyllou, E. (2001). "Two new cases of rank reversals when the AHP and some of its
additive variants are used that do not occur with the Multiplicative AHP." Journal of Multi-Criteria Decision Analysis 10(1): 11-25.
Unfortunately, it is extremely difficult to accurately assess and quantify changing social preferences, and to aggregate conflicting opinions held by diverse social groups. The AnalyticHierarchyProcess (AHP) provides a systematic, explicit, rigorous, and robust mechanism for eliciting and quantifying subjective judgments. It has been applied in many socio-economic planning situations. In the AHP, a hierarchy is used to organize decision-making criteria. Pairwise comparisons are made between criteria at each level of the hierarchy and between possible alternative courses of action (decisions). These comparisons lead to priority vectors which are propagated through the hierarchy to arrive at a final priority vector for the set of decisions alternatives. There are several ways in which the AHP can be used to permit natural resource clientele to engage in participatory decisionmaking. Several types of hierarchies, several hierarchy creation techniques, and two judgment elicitation approaches provide for flexible adaptation of the AHP method. These different scenarios are conceptually described, and brief examples are included from resources management planning and from highway bridge design. The flexibility of the AHP in a variety of decision-making scenarios makes it a useful tool for including disparate participants in a fair and objective manner.
The advancement of technology had encouraged mankind to design and create useful equipments and devices. These equipments enable users to fully utilize them in various applications. Pulp mill is one of the heavy industries that consumes large amount of electricity in its production. Due to this, any malfunction of the equipment might cause mass losses to the company. In particular, the breakdown of the generator would cause other generators to be overloaded. Thus, load shedding scheme is the best way in handling such condition. Selected load will be shed under this scheme in order to protect the generators from being damaged. In the meantime, the subsequence loads will be shed until the generators are sufficient to provide the power to other loads. Once the fault had been fixed, the load shedding scheme can be deactivated. In order to determine the sequences of load shedding scheme, analytichierarchyprocess (AHP) is introduced. AnalyticHierarchyProcess is one of the multi-criteria decision making methods. It had been used in solving a lot of decision making problems since ages ago. AHP is widely used in comparing the options in order to achieve the goal. For the application of AHP in load shedding, the operating load and the area power are chosen to be the criteria. The options of each criterion will be the load of the electrical system in the pulp mill. On the other hand, fuzzy AHP is the advanced version of AHP which can solve the uncertainty of the pair-wise comparison and gives more accurate results in fuzzy situation. This paper presents the alternative methods to choose the load priority in load shedding scheme for a large pulp mill. The results of the AHP and fuzzy AHP analysis to the pulp mill are very promising.
Abstract: AnalyticHierarchyProcess (AHP) is a well-founded and popular method in the Multi-Criteria Decision Analysis (MCDA) field. Recently, AHPSort, a sorting variant, uses crisp class-assignment of alternatives. This can sometimes be misleading, especially for alternatives near the border of two classes. This paper aims at making the class assignment process in AHPSort more flexible by using fuzzy sets theory, which facilitates soft transitions between classes and provides additional information about the membership of alternatives in each class that can be used to fine tune actions beyond the crisp sorting process. This essentially complements the ordinal information of its crisp variant with cardinal information as to the degree of membership of an alternative to each class. The applicability of the proposed approach is illustrated in a case study that regards the classification of London boroughs according to their safety levels.
Bu amaçla, FÜTZ matrisi hiyerarşik bir yapıya dönüştürülmüş ve oluşturulan model Analitik Hiyerarşi Proses (AHP) yöntemiyle çözülmüştür.
Anahtar Kelimeler: SWOT Analizi, Analitik Hiyerarşi Proses.
ABSTRACT: The SWOT analysis is an analysis where external and internal environments of an enterprise are analyzed to find out strategic factors that affect the enterprises’ outcomes. These factors are also used to determine the strategies that would be followed. However, the SWOT analysis bears some insufficiencies with regard to measure and evaluation. It has been put forward in the relevant literature that these insufficiencies could be put aside by analytical approaches. But, only SWOT groups and strategic factors have analytically been dealt with in the previous literature. Deciding on alternative strategies that are based on SWOT factors has not been subject to any study. It is hoped that this study will fill a gap in the relevant literature. In order to fill the gap, the SWOT matrix is converted into a hierarchic structure and the model is analyzed with the AnalyticHierarchyProcess.
Treemaps, a visualization method for large hierarchical data spaces, are used to augment the capabilities of the AnalyticHierarchyProcess (AHP) for decision-making. Two direct manipulation tools, presented metaphorically as a “pump” and a “hook,” were developed and applied to the treemap to support AHP sensitivity analysis. Users can change the importance of criteria dynamically on the two-dimensional treemap and immediately see the impact on the outcome of the decision. This fluid process dramatically speeds up exploration and provides a better understanding of the relative impact of the component criteria. A usability study with 6 subjects using a prototype AHP application showed that treemap representation was acceptable from a visualization and data operation standpoint.
Abstract - An undergraduate curriculum committee has developed the use of the AnalyticHierarchyProcess (AHP) for the evaluation of alternative curriculum designs. The hierarchy consists of four levels of interaction - from the top most objective through affected parties (students, faculty, employers, etc.), curriculum components (design, science, math, etc.), to curriculum alternatives at the bottom. An internet web site has been designed and is being implemented to collect AHP judgments from the affected parties. This collected information can then be used to rank the various curriculum alternatives generated by the committee and others.
In this context, choice means making the correct decisions, selecting the best alternatives and periodically optimizing your choices as the orga- nizational environment changes. The analytichierarchyprocess (AHP) method has proven to be extremely valuable in Six Sigma, lean Six Sigma and other business process improvement prioritization decisions when they involve both tangible and intangible strategic considerations.
The paper shows how the combination of the Early FP estimation method with the quantification technique of subjective judgements, known as AnalyticHierarchyProcess, can result in a enhanced, multi-approach estimation method. The EFP method provides a breakdown, hierarchical structure of the software functional items, while the AHP technique, based on pair-wise comparisons of all the items (and sub-items) of the hierarchy, provides the determination of a ratio scale of relative values between the items, through a mathematical normalization. Consequently, it is not necessary either to evaluate the numerical value of each item, or to use statistical calibration values, since the true values of only one or few components are propagated in the ratio scale of relative values, providing the consistent values for the rest of the hierarchy. This methodological combination can be even improved by using as reference a set of few well-known functions, structured into Catalogues of Functionalities, if present.
Recently, plant construction throughout the world, including nuclear power plant construction, has grown significantly. The scale of Korea’s nuclear power plant con- struction in particular, has increased gradually since it won a contract for a nuclear power plant construction project in the United Arab Emirates in 2009. However, time and monetary resources have been lost in some nuclear power plant construc- tion sites due to lack of risk management ability. The need to prevent losses at nuc- lear power plant construction sites has become more urgent because it demands pro- fessional skills and large-scale resources. Therefore, in this study, the Analytic Hie- rarchy Process (AHP) and Fuzzy AnalyticHierarchyProcess (FAHP) were applied in order to make comparisons between decision-making methods, to assess the poten- tial risks at nuclear power plant construction sites. To suggest the appropriate choice between two decision-making methods, a survey was carried out. From the results, the importance and the priority of 24 risk factors, classified by process, cost, safety, and quality, were analyzed. The FAHP was identified as a suitable method for risk assessment of nuclear power plant construction, compared with risk assessment us- ing the AHP. These risk factors will be able to serve as baseline data for risk man- agement in nuclear power plant construction projects.
2. AnalytichierarchyprocessAnalytichierarchyprocess (AHP) was proposed by T. L. Saaty in 1980 . Its fundamental part consists of pair-wise comparisons of objects on the k th level of hierarchy with regard to objects on the immediately higher (k – 1) th level. Typically, the highest level is a goal, the second level form criteria and the lowest level consists of alternatives. The aim of AHP lies in the selection of the best alternative. As the article focuses on indecisiveness of decision makers in evaluating alternatives, only comparisons of alternatives with regard to a given set of criteria by one or more DMs will be considered.