On the efficacy of modeling multi-attribute decision problems using AHP and Sinarchy

AHP is a multi-attribute decision-making methodology widely used by both practitioners and researchers. In the 1980s, critics had raised questions regarding its proper use. There were quite a few suggested modifications to overcome the supposed limitations of AHP. These modifications are themselves limited as they typically impede the applicability of AHP. In this paper, we revisit some of the earlier criticisms. We have two objectives (1) to articulate the proper use of AHP by highlighting the assumptions and implications underlying AHP, and (2) to show that Sinarchy can be used to address the earlier criticisms while maintaining the applicability of the AHP framework. We identify that in AHP, tradeoffs between criteria vary amongst individual alternatives and are dependent on the alternative’s proportion of contribution towards each criterion. For problems where tradeoffs between criteria are in terms of their relative measurements, Sinarchy should be used. It is also shown that Sinarchy can prevent rank reversal. Illustrative examples are included throughout.     

Does AHP help us make a choice? An experimental evaluation

In this paper, we use experimental economics methods to test how well Analytic Hierarchy Process (AHP) fares as a choice support system in a real decision problem. AHP provides a ranking that we statistically compare with three additional rankings given by the subjects in the experiment: one at the beginning, one after providing AHP with the necessary pair-wise comparisons and one after learning the ranking provided by AHP. While the rankings vary widely across subjects, we observe that for each individual all four rankings are similar. Hence, subjects are consistent and AHP is, for the most part, able to replicate their rankings. Furthermore, while the rankings are similar, we do find that the AHP ranking helps the decision makers reformulate their choices by taking into account suggestions made by AHP.     

层次分析法权重计算方法分析及其应用研究

介绍层次分析法的基本概念,同时也分析了层次分析法权重的计算方法及应用,层次分析法的计算方法有四种方法:几何平均法、算术平均法、特征向量法、最小二乘法,以往的文献利用层次分析法解决实际问题时,都是采用其中的某一种方法求权重向量,不同的方法会导致结果有些偏差,将对一具体实例,采用四种计算方法分别得出权重向量再进行排序和综合分析,这样可以避免采用单一方法所产生的偏差,得出的结论将更全面、更有效。     

Another potential shortcoming of AHP

In the last twenty years many features of Saaty’s Analytical Hierarchy Process (AHP) have been criticised, especially the additive hierarchical composition of conventional AHP, which leads to the possibility of occurrence of the Rank Reversal phenomenon (adding an irrelevant alternative may cause a reversal in the ranking at the top). In this paper we show another feature of AHP which may be, and in many application contexts will inneed be, an even stronger shortcoming of the method. It consists in the fact that the addition of indifferent criteria (for which all alternatives perform equally) causes a significant alteration of the aggregated priorities of alternatives, with important consequences. In hierarchies with four or more levels, rank reversal may happen. Since in almost all applications of AHP the set of criteria is not fixed ex-ante but is variable and is constructed in accordance with reasons of relevance and simplicity, almost all applications of AHP are potentially flawed.     

A new data envelopment analysis method for priority determination and group decision making in the analytic hierarchy process

The DEAHP method for weight deviation and aggregation in the analytic hierarchy process (AHP) has been found flawed and sometimes produces counterintuitive priority vectors for inconsistent pairwise comparison matrices, which makes its application very restrictive. This paper proposes a new data envelopment analysis (DEA) method for priority determination in the AHP and extends it to the group AHP situation. In this new DEA methodology, two specially constructed DEA models that differ from the DEAHP model are used to derive the best local priorities from a pairwise comparison matrix or a group of pairwise comparison matrices no matter whether they are perfectly consistent or inconsistent. The new DEA method produces true weights for perfectly consistent pairwise comparison matrices and the best local priorities that are logical and consistent with decision makers (DMs)’ subjective judgments for inconsistent pairwise comparison matrices. In hierarchical structures, the new DEA method utilizes the simple additive weighting (SAW) method for aggregation of the best local priorities without the need of normalization. Numerical examples are examined throughout the paper to show the advantages of the new DEA methodology and its potential applications in both the AHP and group decision making.     

Analytic hierarchy process: An overview of applications

This article presents a literature review of the applications of Analytic Hierarchy Process (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 references are summarized in various tabular formats and charts.A total of 150 application papers are referred to in this paper, 27 of them are critically analyzed. It is hoped that this work will provide a ready reference on AHP, and act as an informative summary kit for the researchers and practitioners for their future work.     

Fuzzy analytic hierarchy process: Fallacy of the popular methods

The fuzzy Analytic Hierarchy Process (fuzzy AHP) is a very popular decision making method and literally thousands of papers have been published about it. However, we find the basic logic of this approach has problems. From its methodology, the definition and operational rules of fuzzy numbers not only oppose the main logic of fuzzy set theory, but also oppose the basic principles of the AHP. In dealing with the outcomes, fuzzy AHP does not give a generally accepted method to rank fuzzy numbers and a way to check the validity of the results. Besides, we discuss the validity of the Analytic Hierarchy/Network Process (AHP/ANP) in complex and uncertain environments and find that fuzzy ANP is a false proposition because there is no fuzzy priority in the super matrix which provides the basis for the ANP. Although fuzzy AHP has been applied in many cases and cited hundreds of times, we hoped that those who use fuzzy AHP would understand the problems associated with this method.     

层次分析法在湖南省粮食生产发展对策分析中的应用

本文综述了层次分析法的基本原理和过程，建立了湖南省粮食生产发展对策分析的层次分析模型，对影响湖南省粮食生产发展的多种因素进行了综合排序，其结果有一定的实际指导意义．     

Numerical scales generated individually for analytic hierarchy process

Because individual interpretations of the analytic hierarchy process (AHP) linguistic scale vary for each user, this study proposes a novel framework that AHP decision makers can use to generate numerical scales individually, based on the 2-tuple linguistic modeling of AHP scale problems. By using the concept of transitive calibration, individual characteristics in understanding the AHP linguistic scale are first defined. An algorithm is then proposed for detecting the individual characteristics from the linguistic pairwise comparison data that is associated with each of the AHP individual decision makers. Finally, a nonlinear programming model is proposed to generate individual numerical scales that optimally match the obtained individual characteristics. Two well-known numerical examples are re-examined using the proposed framework to demonstrate its validity.     

DS/AHP method: A mathematical analysis,including an understanding of uncertainty

The analytic hierarchy process (AHP) was developed to aid decision makers to rank or sort information based on a number of criteria. A recent advance is the DS/AHP method which incorporates the Dempster–Shafer theory of evidence with AHP. This method allows judgements on groups of decision alternatives (DA) to be made, it also offers a measure of uncertainty in the final results. In this paper a mathematical analysis of DS/AHP is included, constructing the functional form of the preference weightings given to groups of DA. These functions allow an understanding of the appropriateness of the rating scale values used in the DS/AHP method, through evaluating the range of uncertainty able to be expressed by the decision maker.     

Scale transitivity in the AHP

Transitivity is important in multicriteria decision-making. The analytic hierarchy process (AHP), as one of the widely used decision analysis tools, is criticized since it suffers from scale intransitivity. This paper first reviews and compares different scales from different aspects, then discusses the transitivity of AHP scales and derives a scale based on the transitivity, so it is naturally transitive. Besides, two approaches are provided to determine the scale parameter for the derived transitive scale. In order to deal with the transitivity problem, the AHP provides a consistency index for testing pairwise comparison consistency. So, finally, this paper proposes a consistency measure to reflect the judgmental inconsistency.     

An intrinsic consistency threshold for reciprocal matrices

In this paper we present a new, intrinsic and scale independent consistency threshold for reciprocal matrices in the Analytic Hierarchy Process (AHP). Its derivation is based upon the relation between the consistency measure of the AHP and the reduction of weight of a new alternative. We compare this standard with an existing one.     

基于DS/AHP的供应商选择方法

供应商选择方法有很多种，在众多的方法中层次分析法以能够将定性指标定量化而被广泛应用于供应商选择决策中。考虑到供应商选择问题中包含有很多的不确定性而证据理论在处理不确定问题又有着独特的优点，因此本文采用了一种由层次分析法和证据理论结合而产生的DS／AHP决策方法，并将其应用于供应商选择决策问题中，该方法综合了层次分析法和证据理论的优点，可以更科学的进行供应商选择决策，最后通过一个例子说明这种方法在供应商选择中的应用。     

A Thurstonian view of the analytic hierarchy process

The application of deterministic decision models in situations characterized by noise and uncertainty is likely to produce results of questionable value. In this paper, some very simple probabilistic models are developed and substituted for the deterministic scales used in the Analytic Hierarchy Process (AHP). It is shown that the use of these probabilistic models can extend the domain of AHP to situations, such as consensual or group decision making, that possess significant amounts of uncertainty. In addition, explicit measures of the variation present in the evaluation of decision alternatives and attributes are obtained.     

Group decision making in a multiple criteria environment: A case using the AHP in software selection

This paper reports the results of a case study where the analytic hierarchy process (AHP) technique was employed to support the selection of a multi-media authorizing system (MAS) in a group decision environment. Three MAS products were identified and ultimately ranked using the AHP. Six software engineers, who are technically competent and experienced, participated in our study. These engineers were trained to use the AHP and asked to apply this technique to select the most appropriate MAS product for adoption. A post-study survey and interview were conducted with all the engineers to collect further feedback on the use of the AHP, as compared to their frequently used Delphi technique, in supporting group decisions. The experiment results and survey findings indicated that the AHP is preferable to Delphi as the AHP helps group members center a discussion around objectives, rather than alternatives. We also found the AHP to be more conducive to consensus building in group decision settings.     

Fuzzy logic modifications of the Analytic Hierarchy Process

The Analytic Hierarchy Process (AHP) is a measurement methodology based on pair-wise comparisons that relies on judgment to derive priority scales. During its implementation, one constructs hierarchies, then makes judgments or performs measurements on pairs of elements with respect to a criterion to derive preference scales, which are then synthesized throughout the structure to select the preferred alternative.One of the areas where the AHP finds application is in the subjective phases of risk assessment (RA), where it is used to structure and prioritize diverse risk factors, including the judgments of experts. Since fuzzy logic (FL) has been shown to be an effective tool for accommodating human experts and their communication of linguistic variables, there has been research aimed at modeling the fuzziness in the AHP (FAHP), and recently the focus of some of that modeling has been with respect to RA.The literature discusses more than one FAHP model, which raises the question as to which are the prominent models and what are their characteristics. In response to this question, we examine three of the most influential FAHP models. The article proceeds as follows. It begins with a brief overview of the AHP and its limitations when confronted with a fuzzy environment. This is followed by a discussion of FL modifications of the AHP. A RA-based likelihood score example is used throughout. The article ends with a commentary on the findings.     

AHP方法一致性检验的新标准

在层次分析法中判断矩阵是否具有满意的一致性是一个重要的问题.对一致性差的判断矩阵,首先利用F-范数定义了s_k,然后讨论了s_k的单调性,从而随着对判断矩阵元素的调整,对判断矩阵一致性度量给出一个新的参考标准.     

A combined approach for fuzzy multi-objective multiple knapsack problems for defence project selection

In this study, a model representing military requirements as scenarios and capabilities is offered. Pair-wise comparisons of scenarios are made according to occurrence probabilities by using the Analytical Hierarchy Process (AHP). The weights calculated from AHP are used as the starting weights in a Quality Function Deployment (QFD) matrix. QFD is used to transfer war fighter requirements into the benefit values of projects. Two levels of QFD matrices are used to evaluate new capability areas versus capabilities and capabilities versus projects. The benefit values of the projects are used in a multi-objective problem (multi-objective multiple knapsack problem) that considers the project benefit, implementation risks and environmental impact as multiple objectives. Implementation risk and environmental impact values are also calculated using the same combined AHP and QFD methodology. Finally, the results of the fuzzy multi-objective goal programming suggest a list of projects that offers optimal benefit when carried out within multiple budgets.     

Methods based on data envelopment analysis for deriving group priorities in analytic hierarchy process

In recent years, group decision making has become one of the important issues in multiple criteria decision making, and analytic hierarchy process (AHP) is considered an appropriate method when dealing with this kind of problems. Many different approaches for attaining a group valuation in AHP have been developed. The applications most commonly employ the weighted geometric mean method. In the paper, we focus on the group AHP methods, which are based on the data envelopment analysis (DEA). First we discuss two methods for deriving a group priority vector: Wang and Chin’s DEA group method and Hosseinian et al.’s DEA-WDGD. Further, we propose a new WGMDEA method and compare all three methods with the WGMM on theoretical examples and on a real case study. The objective of the case study is to examine the current state of forest owners’ cooperatives. An analysis of the influence of forest owners’ cooperatives on private forest management in Slovenia was put forward. The A’WOT analysis, which is a combined method of AHP and SWOT analysis, an approach for identifying the strengths, weaknesses, opportunities and threats of the object under consideration, was performed.     

AHP一致性的概率检验法

Saaty的层次分析决策方法(AHP)是目前较为流行的多属性目标决策方法.AHP方法的一致性问题是其理论研究中心之一.通过Saaty的判断属性集合和一致性水平,很容易验证判断矩阵的一致性程度是否满足.但是对于Saaty的一致性水平,要求C.R≤0.1的内涵还需要进一步的揭示.研究Saaty的一致性原理,并给出检验矩阵一致性的概率方法,简称α一致性方法.